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3 Semester - 2022 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
CS331P | DATABASE MANAGEMENT SYSTEMS | Core Courses | 5 | 4 | 100 |
CS332P | DATA STRUCTURES AND ALGORITHMS | Core Courses | 5 | 4 | 100 |
CS333 | SOFTWARE ENGINEERING | Core Courses | 3 | 3 | 100 |
CSHO331AIP | STATISTICAL FOUNDATION FOR ARTIFICIAL INTELLIGENCE | Minors and Honours | 5 | 4 | 100 |
CSHO331CSP | PROBABILITY AND RANDOM PROCESS | Minors and Honours | 5 | 4 | 100 |
CSHO331DAP | STATISTICAL FOUNDATION FOR DATA ANALYTICS | Minors and Honours | 5 | 4 | 100 |
CY321 | CYBER SECURITY | Skill Enhancement Courses | 2 | 0 | 0 |
EC337 | DIGITAL SYSTEMS | Core Courses | 3 | 3 | 100 |
HS311 | TECHNICAL WRITING | Core Courses | 2 | 2 | 50 |
MA334 | DISCRETE MATHEMATICS | Core Courses | 3 | 3 | 100 |
VCSE111 | PCAP PROGRAMMING ESSENTIALS IN PYTHON | - | 4 | 0 | 100 |
VCSE314 | JAVA PROGRAMMING | - | 4 | 0 | 100 |
VCSE315 | RED HAT CERTIFIED SYSTEM ADMINISTRATOR | - | 4 | 0 | 100 |
4 Semester - 2022 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
BS451 | BIOLOGY FOR ENGINEERS LABORATORY | - | 2 | 1 | 50 |
CS432P | OPERATING SYSTEMS | - | 5 | 4 | 100 |
CS433P | PROGRAMMING PARADIGM | - | 5 | 4 | 100 |
CS434 | FORMAL LANGUAGE AND AUTOMATA THEORY | - | 3 | 3 | 100 |
CS435P | COMPUTER ORGANIZATION AND ARCHITECTURE | - | 5 | 4 | 100 |
CSHO432AIP | ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING | - | 5 | 4 | 100 |
CSHO432CSP | MOBILE AND NETWORK BASED ETHICAL HACKING | - | 5 | 4 | 100 |
CSHO432DAP | BIG DATA ANALYTICS | - | 5 | 4 | 100 |
EVS421 | ENVIRONMENTAL SCIENCE | - | 2 | 0 | 0 |
HS422 | PROFESSIONAL ETHICS | - | 2 | 2 | 50 |
MA431 | PROBABILITY AND QUEUING THEORY | - | 3 | 3 | 100 |
5 Semester - 2021 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
CS531P | COMPUTER NETWORKS | Core Courses | 5 | 4 | 100 |
CS532 | INTRODUCTION TO ARTIFICIAL INTELLIGENCE | Core Courses | 3 | 3 | 100 |
CS533P | DESIGN AND ANALYSIS OF ALGORITHMS | Core Courses | 5 | 4 | 100 |
CS541E01 | COMPUTER GRAPHICS WITH OPEN GL | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS541E02 | INTERNET AND WEB PROGRAMMING | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS541E04 | CRYPTOGRAPHY AND NETWORK SECURITY | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS581 | INTERNSHIP - I | Project | 2 | 1 | 50 |
CSHO533AIP | ROBOTICS AND PROCESS AUTOMATION | Minors and Honours | 5 | 4 | 100 |
CSHO533CSP | CYBER FORENSICS AND MALWARE DETECTION | Minors and Honours | 5 | 4 | 100 |
CSHO533DAP | BIG DATA SECURITY ANALYTICS | Minors and Honours | 5 | 4 | 100 |
CSHO534AIP | COMPUTER VISION | Minors and Honours | 5 | 4 | 100 |
CSHO534CSP | INTRUSION DETECTION AND INCIDENT RESPONSE | Minors and Honours | 5 | 4 | 100 |
CSHO534DAP | WEB ANALYTICS | Minors and Honours | 5 | 4 | 100 |
ECOE5601 | EMBEDDED BOARDS FOR IOT APPLICATIONS | Interdisciplinary Elective Courses | 3 | 3 | 100 |
ECOE5602 | FUNDAMENTALS OF IMAGE PROCESSING | Interdisciplinary Elective Courses | 3 | 3 | 100 |
ECOE5603 | OBSERVING EARTH FROM SPACE | Interdisciplinary Elective Courses | 3 | 3 | 100 |
EEOE531 | HYBRID ELECTRIC VEHICLES | Interdisciplinary Elective Courses | 4 | 3 | 100 |
EEOE532 | ROBOTICS AND AUTOMATION | Interdisciplinary Elective Courses | 4 | 3 | 100 |
EEOE533 | SMART GRIDS | Interdisciplinary Elective Courses | 3 | 3 | 100 |
HS521 | PROJECT MANAGEMENT AND FINANCE | Discipline Specific Elective Courses | 3 | 3 | 100 |
IC521 | CONSTITUTION OF INDIA | Skill Enhancement Courses | 2 | 0 | 50 |
IT541E01 | UNIX AND SHELL PROGRAMMING | Discipline Specific Elective Courses | 3 | 3 | 100 |
NCCOE1 | NCC1 | Interdisciplinary Elective Courses | 3 | 3 | 100 |
VCSE514 | CCNA: INTRODUCTION TO NETWORKS (ITN) | - | 4 | 0 | 100 |
VCSE516 | FULL STACK WEB DEVELOPMENT | - | 4 | 0 | 100 |
6 Semester - 2021 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
BTGE631 | CORPORATE SOCIAL RESPONSIBILITY | - | 2 | 2 | 100 |
BTGE632 | DIGITAL MEDIA | - | 2 | 2 | 100 |
BTGE633 | FUNCTIONAL ENGLISH | - | 2 | 2 | 100 |
BTGE634 | GERMAN | - | 2 | 2 | 100 |
BTGE635 | INTELLECTUAL PROPERTY RIGHTS | - | 2 | 2 | 100 |
BTGE636 | INTRODUCTION TO AVIATION | - | 2 | 2 | 100 |
BTGE637 | PROFESSIONAL PSYCHOLOGY | - | 2 | 2 | 100 |
BTGE651 | DATA ANALYTICS THROUGH SPSS | - | 2 | 2 | 100 |
BTGE652 | DIGITAL MARKETING | - | 2 | 2 | 100 |
BTGE653 | DIGITAL WRITING | - | 2 | 2 | 100 |
BTGE654 | PHOTOGRAPHY | - | 2 | 2 | 100 |
BTGE655 | ACTING COURSE | - | 2 | 2 | 100 |
BTGE656 | CREATIVITY AND INNOVATION | - | 2 | 2 | 100 |
BTGE657 | PAINTING AND SKETCHING | - | 2 | 2 | 100 |
BTGE658 | DESIGN THINKING | - | 2 | 2 | 100 |
CS631P | INTERNET OF THINGS | - | 5 | 4 | 100 |
CS632P | COMPILER DESIGN | - | 5 | 4 | 100 |
CS642E01 | MOBILE APPLICATION DEVELOPMENT | - | 3 | 3 | 100 |
CS642E03 | ADVANCED DATABASES | - | 3 | 3 | 100 |
CS642E06 | SYSTEM SOFTWARE | - | 3 | 3 | 100 |
CS681 | SERVICE LEARNING | - | 2 | 2 | 50 |
CSHO681AIP | AI PROJECT /CERTIFICATE COURSES | - | 5 | 4 | 100 |
CSHO681CSP | CS PROJECT/CERTIFICATE COURSES | - | 5 | 4 | 100 |
CSHO681DAP | DA PROJECT/CERTIFICATE COURSES | - | 5 | 4 | 100 |
IT633P | DATA WAREHOUSING AND DATA MINING | - | 5 | 4 | 100 |
IT642E02 | FOUNDATIONS TO BLOCKCHAIN TECHNOLOGY | - | 3 | 3 | 100 |
MIIMBA634 | DATA ANALYSIS FOR MANAGERS | - | 3 | 4 | 100 |
7 Semester - 2020 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
CEOE731 | SUSTAINABLE AND GREEN TECHNOLOGY | Interdisciplinary Elective Courses | 3 | 3 | 100 |
CEOE732 | AIR POLLUTION AND CONTROL | Interdisciplinary Elective Courses | 3 | 03 | 100 |
CEOE733 | GIS AND REMOTE SENSING TECHNIQUES AND APPLICATIONS | Interdisciplinary Elective Courses | 3 | 3 | 100 |
CS743E02 | TCP/IP DESIGN AND IMPLEMENTATION | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS743E03 | SIMULATION AND MODELING | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS743E04 | SOFTWARE PROCESS AND PROJECT MANAGEMENT | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS743E08 | SOFTWARE PROJECT MANAGEMENT | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS744E01 | INFORMATION STORAGE AND MANAGEMENT | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS744E02 | DATA BASE ADMINISTRATION | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS744E03 | NETWORK STORAGE TECHNOLOGIES | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS744E04 | NETWORK ADMINISTRATION | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS744E05 | RESEARCH METHODOLOGY | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS745E01 | QUANTUM COMPUTING | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS745E02 | MOBILE COMPUTING | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS745E05 | CLOUD COMPUTING | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS781 | INTERNSHIP - II | Project | 2 | 1 | 50 |
CS782 | PROJECT WORK PHASE I | Project | 8 | 4 | 100 |
CSHO731AIP | COMPUTER VISION | Interdisciplinary Elective Courses | 5 | 4 | 100 |
CSHO731DAP | WEB ANALYTICS | Minors and Honours | 5 | 4 | 100 |
CSHO781AIP | AI PROJECT/ MOOC COURSE/ CERTIFIED COURSE | Minors and Honours | 5 | 4 | 100 |
CSHO781DAP | DA PROJECT / CERTIFICATE COURSES | Minors and Honours | 5 | 4 | 100 |
ME761E03 | BASIC AUTOMOBILE ENGINEERING | Interdisciplinary Elective Courses | 3 | 3 | 100 |
ME761E04 | SMART MATRIALS AND APPLICATIONS | Interdisciplinary Elective Courses | 3 | 3 | 100 |
NCCOE2 | NCC2 | Interdisciplinary Elective Courses | 3 | 3 | 100 |
PH736OE1 | NANO MATERIALS AND NANOTECHNOLOGY | Interdisciplinary Elective Courses | 3 | 3 | 100 |
8 Semester - 2020 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
CS846E01 | COMPUTER AIDED DECISION SUPPORT SYSTEMS | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS846E04 | HIGH PERFORMANCE COMPUTING | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS846E07 | NATURAL LANGUAGE PROCESSING | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS881 | PROJECT WORK PHASE II | Project | 20 | 10 | 300 |
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The Undergraduate program in Information Technology is aimed at creating computer science engineers by providing the fundamentals of engineering and basic skills in computing. The special focus on employability is clear from the inclusion of subjects based on demand of industry and mandatory internships. A well-chosen elective basket gives the ward an opportunity to widen their knowledge in any specific domain. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Programme Outcome/Programme Learning Goals/Programme Learning Outcome: PO1: Apply Engineering knowledge of computing, mathematics, science, and computer science & engineering fundamentals for Problem solving.PO2: Think critically to identify, formulate, and solve complex computer science & engineering problems by developing models, evaluating validity and accuracy of solutions in terms of computer science and engineering validity measures. PO3: Analyse, design of complex problems, implement, and evaluate a computer-based system, to meet expected needs with appropriate considerations such as economic / environmental/societal. PO4: Conduct experiments to investigate problems based on changing requirements, analyze and interpret results. PO5: Create, select, adapt appropriate techniques and use of the modern computational tools, techniques and skills, and best of engineering practices. PO6: Understand the impact of contextual knowledge on social aspects and cultural issues. PO7: Understand contemporary issues related to social & environmental context for sustainable development of engineering solutions. PO8: Understand professional & ethical responsibility to contribute for societal and national needs. PO9: Function and coordinate effectively as an individual, as a member or leader in diverse, multicultural& multidisciplinary teams PO10: Communicate effectively. PO11: Demonstrate an understanding of computer science and engineering & management principles to manage software projects. PO12: Demonstrate a recognition and realization of the need for, and an ability to engage in lifelong learning. Programme Specific Outcome: PSO1: Project Management and Development: Develop and Manage Software Applications through suitable validation methodology.PSO2: Design feasible software solutions through data science. PSO3: Analyze Social Relevant Problems and Design Software /IT based solutions through Service Learning. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Assesment Pattern | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
II. ASSESSMENT - ONLY FOR THEORY COURSE (without practical component)
Components of the CIA CIA I: Subject Assignments / Online Tests: 10 marks CIA II: Mid Semester Examination (Theory): 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications: 10 marks Attendance: 05 marks Total: 50 marks
Mid Semester Examination (MSE) : Theory Papers:
End Semester Examination (ESE): The ESE is conducted for 100 marks of 3 hours duration. The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution. Question paper pattern is as follows. Two full questions with either or choices will be outlined from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a particular question. The objective of the question paper is to test the application and analytical skill of the student. The major purpose of the question paper is to bring clarity about the process of associating questions to their respective performance indicators and hence to improve the ratings in course outcomes. Further, these question papers demonstrate how bloom’s taxonomy can be used to map the quality of question papers along with their effectiveness in the assessment pattern.
III. ASSESSMENT OF COMPREHENSION, INTERNSHIP and SERVICE LEARNING COMPREHENSION Maximum Marks = 50 Passing marks 40% min Do not have ESE and completely evaluated through continuous assessment only,
The evaluation (minimum 2 presentations) shall be based on the
INTERNSHIP
Maximum Marks = 50(Only credit will be displayed in the score card) Passing marks 40% min Do not have ESE and completely evaluated through continuous assessment only Continuous Internal Assessment is based upon
SERVICE LEARNING Maximum Marks = 50 Passing marks 40% min Do not have ESE and completely evaluated through continuous assessment only, Comprising
V. ASSESSMENT OF PROJECT WORK Project Phase-I Project work may be assigned to a single student (with due approval from department) or to a group of students not exceeding 4 per group. Maximum Marks = 100
ESE 100 MARKS IS EVALUATED AS
Holistic Education: End Semester Examination :25 Marks Participation:25 Marks
Total :50 Marks
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Examination And Assesments | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Continuous internal Assesment-CIA-I,CIA-II,CIA-III End Semester Examination |
CS331P - DATABASE MANAGEMENT SYSTEMS (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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To learn the fundamentals of data models and to conceptualize and depict a database system using ER diagram. To make a study of SQL and relational database design. To understand the internal storage structures using different file and indexing techniques which will help in physical DB design. To know the fundamental concepts of transaction processing- concurrency control techniques and recovery procedure. To have an introductory knowledge about the emerging trends in the area of distributed DBOO DB- Data mining and Data Warehousing and XML. To implement the design of the tables in DBMS. To write queries to get optimized outputs. To store, retrieve and view the contents. To generate report based on customized need |
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Course Outcome |
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C01: Apply the Conepts of Entity-Relationship (E-R) model for the given application. CO2: Apply Normalization principles to create and maniplulate relational databases CO3: Apply the concepts of Non-Relational Models CO4: Examine different file organization concepts for data storage in Relational databases CO5: Apply the transaction management principles on relational databases |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION AND CONCEPTUAL MODELING
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Introduction to File and Database systems- Database system structure – Data Models – Introduction to Network and Hierarchical Models – ER model – Relational Model – Relational Algebra. | |
Unit-2 |
Teaching Hours:9 |
RELATIONAL MODEL
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SQL – Data definition- Queries in SQL- Updates- Views – Integrity and Security – Relational Database design – Functional dependencies and Normalization for Relational Databases (up to BCNF). | |
Unit-3 |
Teaching Hours:9 |
NON RELATIONAL MODEL
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Introduction to NOSQL Systems ,The CAP Theorem, Document-Based NOSQL Systems and MongoDB, NOSQL Key-Value Stores, Column-Based or Wide Column NOSQL Systems, NOSQL Graph Databases and Neo4j | |
Unit-4 |
Teaching Hours:9 |
DATA STORAGE AND QUERY PROCESSING
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Record storage and Primary file organization- Secondary storage Devices- Operations on FilesHeap File- Sorted Files- Hashing Techniques – Index Structure for files –Different types of Indexes- B-Tree - B+ Tree – Query Processing. | |
Unit-5 |
Teaching Hours:9 |
TRANSACTION MANAGEMENT
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Transaction management -Transaction Processing – Introduction- Need for Concurrency control- Desirable properties of Transaction- Schedule and Recoverability- Serializability and Schedules – Concurrency Control – Types of Locks- Two Phases locking- Deadlock- Time stamp based concurrency control – Recovery Techniques – Concepts- Immediate Update- Deferred Update - Shadow Paging. | |
Text Books And Reference Books: Abraham Silberschatz, Henry F. Korth and S. Sudarshan- “Database System Concepts”, Seventh Edition, McGraw-Hill, 2021 | |
Essential Reading / Recommended Reading Andreas Meier · Michael Kaufmann "SQL & NoSQL Databases", Springer -2019 Raghu Ramakrishnan, “Database Management System”, Tata McGraw-Hill Publishing Company, 2003 Online Resources: W1.http://db-book.com/db6/slide-dir | |
Evaluation Pattern CIA:70/100 ESE:30/100 | |
CS332P - DATA STRUCTURES AND ALGORITHMS (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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To understand the basic concept of data structures for storage and retrieval of ordered or unordered data. Data structures include: arrays, linked lists, binary trees, heaps, and hash tables. |
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Course Outcome |
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CO1: Implement various ADT and Calculate the complexity of the algorithm CO2: Experiment with various operations on Linear Data structures CO3: Experiment with various Non- Linear Data structures and Hashing techniques CO4: Compare different sorting techniques with respect to time complexity CO5: Make use of graph algorithms in various applications of graph traversal, shortest path and sorting techniques. |
Unit-1 |
Teaching Hours:11 |
INTRODUCTION and STACK ADT
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Definition- Classification of data structures: primitive and non-primitive- Operations on data structures- Algorithm Analysis: Introduction. The Stack ADT: Definition, Array representation of stack, Operations on stack: Infix, prefix and postfix notations Conversion of an arithmetic Expression from Infix to postfix. Applications of stacks. | |
Unit-2 |
Teaching Hours:14 |
LISTS AND QUEUES
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The Queue ADT: Definition, Array representation of queue, Types of queues: Simple queue, circular queue, double ended queue (de-queue) priority queue, operations on all types of Queues. The List ADT: singly linked list implementation, insertion, deletion and searching operations on linear list, circular linked list implementation, Double linked list implementation, insertion, deletion and searching operations. Applications of linked lists. | |
Unit-3 |
Teaching Hours:13 |
TREES
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Preliminaries – Binary Trees – The Search Tree ADT – Binary Search Trees – AVL Trees – Tree Traversals – Hashing – General Idea – Hash Function – Separate Chaining – Open Addressing –Linear Probing – Priority Queues (Heaps) – Model – Simple implementations – Binary Heap | |
Unit-4 |
Teaching Hours:20 |
SORTING
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Preliminaries – Insertion Sort, Selection sort – Shell sort – Heap sort – Merge sort – Quicksort – External Sorting | |
Unit-5 |
Teaching Hours:14 |
GRAPHS
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Introduction to Graphs, Definitions –DFS, BFS, Minimum Spanning Tree – Prim’s and Kruskal's Algorithm. Single-Source Shortest Paths – Bellman-Ford algorithm and Dijkstra’s Algorithm – Applications of Graphs | |
Text Books And Reference Books: T1. Mark Allen Weiss, “Data Structures and Algorithm Analysis in C”, 3rd Edition, Pearson Education 2013. | |
Essential Reading / Recommended Reading R1. Fundamentals of data structure in C by Ellis Horowitz, Sarataj Shani 3rd edition, Galgotia book source PVT,2010. R2. Classic Data Structures , Debasis Samanta ,2nd Edition, PHI Learning PVT,2011 | |
Evaluation Pattern CIA-70/100 ESE-30/100 | |
CS333 - SOFTWARE ENGINEERING (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course Description: Software engineering course provides: Different life cycle models, Requirement dictation process, Analysis modelling and specification, Architectural and detailed design methods, Implementation and testing strategies, Verification and validation techniques, Project planning and management and Use of CASE tools. Course objectives: To be aware of Different life cycle models; Requirement dictation process; Analysis modeling and specification; Architectural and detailed design methods; Implementation and testing strategies; Verification and validation techniques; Project planning and management and Use of CASE tools. |
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Course Outcome |
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CO1: Explain the fundamental of Software development Life cycle and different software development process models. CO2: Describe various requirement elicitation methods in software development process. CO3: Choose the software processes and concepts using various design technique CO4: Make use of different testing techniques and maintenance principles in software development process. CO5: Identify the cost estimation techniques and project scheduling methods in software development process. |
Unit-1 |
Teaching Hours:9 |
SOFTWARE PROCESS
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Introduction –S/W Engineering Paradigm – life cycle models (water fall, incremental, spiral, WINWIN spiral, evolutionary, prototyping, object oriented) - system engineering – computer based system – verification – validation – life cycle process – development process –system engineering hierarchy. | |
Unit-2 |
Teaching Hours:9 |
SOFTWARE REQUIREMENTS
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Functional and non-functional - user – System –requirement engineering process – feasibility studies – requirements – elicitation – validation and management – software prototyping – prototyping in the software process – rapid prototyping techniques – user interface prototyping -S/W document. Agile methods, Extreme Programming, SCRUM. | |
Unit-3 |
Teaching Hours:9 |
DESIGN CONCEPTS AND PRINCIPLES
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Design process and concepts – Modular design – design heuristic – design model and document. Architectural design – software architecture – data design – architectural design – transform and transaction mapping – user interface design – user interface design principles-Model representation- Real time systems - Real time software design – system design – real time executives – data acquisition system - monitoring and control system. SCM – Need for SCM – Version control – Introduction to SCM process – Software configuration items. | |
Unit-4 |
Teaching Hours:9 |
TESTING
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Taxonomy of software testing – levels – test activities – types of s/w test – black box testing – testing boundary conditions – structural testing – test coverage criteria based on data flow mechanisms – regression testing – testing in the large. S/W testing strategies – strategic approach and issues - unit testing – integration testing – validation testing – system testing and debugging. | |
Unit-5 |
Teaching Hours:9 |
SOFTWARE PROJECT MANAGEMENT
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Measures and measurements – S/W complexity and science measure – size measure – data and logic structure measure – information flow measure. Software cost estimation – function point models – COCOMO model- Delphi method.- Defining a Task Network – Scheduling – Earned Value Analysis – Error Tracking - Software changes – program evolution dynamics – software maintenance – Architectural evolution. Taxonomy of CASE tools – Agile based Case Study. | |
Text Books And Reference Books: Roger S. Pressman, Bruce Maxim, Software engineering- A Practitioner’s Approach, McGraw-Hill International Edition, 9th Edition 2020 | |
Essential Reading / Recommended Reading R1. Roger S. Pressman, Software engineering- A Practitioner’s Approach, McGraw-Hill International Edition, 6th Edition 2014.. R2. Ian Sommerville, “Software engineering,” Pearson education Asia, 9th Edition, 2013. R3. Pankaj Jalote- “An Integrated Approach to Software Engineering,” Narosa Publishing house, 2011. R4.James F Peters and Witold Pedryez, “Software Engineering – An Engineering Approach”, John Wiley and Sons, New Delhi, 2010. R5.Ali Behforooz and Frederick J Hudson, “Software Engineering Fundamentals”, OUP India 2012.
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Evaluation Pattern Continuous Internal Assessment CIA Marks 50 End Semester Exams ESE 50 Total 100 | |
CSHO331AIP - STATISTICAL FOUNDATION FOR ARTIFICIAL INTELLIGENCE (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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● Discuss the core concepts Statistical Analytics and Data manipulation ● Apply the basic principles, models, and algorithms supervised and unsupervised learning mechanisms. ● Analyse the structures and algorithms of regression methods ● Analyse the use of SVM in Data Science Explain notions and theories associated to Convolutional Neural Networks |
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Course Outcome |
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CO 1: Demonstrate concepts associated to Statistical Analytics and Data manipulation CO 2: Experiment with Data Visualization, Statistical Graphics and Statistical Inference. CO 3: Solve Problems related to Statistical Learning and Data Analytics CO 4: Make use of Supervised learning to solve real life problems CO 5: Apply Supervised, Unsupervised and Ensemble learning to solve real life problems. |
Unit-1 |
Teaching Hours:9 |
STATISTICAL ANALYTICS AND DATA MANIPULATION
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Knowledge discovery: finding structure in data, Data quality versus data quantity, Statistical modeling versus statistical description. Data types, Data summarization, Means, medians, and central tendency, Summarizing variation, Summarizing (bivariate) correlation, Data diagnostics and data transformation, Outlier analysis, Entropy, Data transformation Simple smoothing techniques, Binning, Moving averages, Exponential smoothing. Introduction to SPSS (IBM’s) statistical tool. | |
Unit-2 |
Teaching Hours:9 |
TECHNIQUES FOR SUPERVISED AND UNSUPERVISED LEARNING
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The simple linear model, Multiple inferences and simultaneous confidence bands, Regression diagnostics, Weighted least squares (WLS) regression, Correlation analysis. Unsupervised versus supervised learning, Principal component analysis, Principal components, Implementing a PCA, Exploratory factor analysis. | |
Unit-3 |
Teaching Hours:9 |
NEURAL NETWORKS
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Projection Pursuit Regression, Neural Networks, Fitting Neural Network, Some Issues in Training Neural Networks, Bayesian Neural Nets, 0 Computational Considerations. | |
Unit-4 |
Teaching Hours:9 |
SUPPORT VECTOR MACHINES AND FLEXIBLE DISCRIMINANTS
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Introduction, The Support Vector Classifier, Support Vector Machines and Kernels, Generalizing Linear Discriminant Analysis, Flexible Discriminant Analysis, Penalized Discriminant Analysis, Mixture Discriminant Analysis | |
Unit-5 |
Teaching Hours:9 |
RANDOM FORESTS AND ENSEMBLE LEARNING
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Definition of Random Forests, Details of Random Forests- Out of Bag Samples, Variable Importance, Proximity Plots; Analysis of Random Forests; Ensemble Learning, Boosting and Regularization Paths, Learning a Good Ensemble, Rule Ensembles. | |
Text Books And Reference Books: T1. Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media, 2017. T2. Russell, Stuart J., and Peter Norvig. Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited,, 2016. | |
Essential Reading / Recommended Reading R1. Ghahramani, Zoubin. "Probabilistic Machine Learning and Artificial Intelligence." Nature521.7553 (2015): 452. R2. Ian Goodfellow and Yoshua Bengio and Aaron Courville,” Deep Learning ”, MIT Press, March 2018. R3. Wu, James, and Stephen Coggeshall. Foundations of predictive analytics. Chapman and Hall/CRC, 2012. R4. Marcoulides, George A., and Scott L. Hershberger. Multivariate statistical methods: A first course. Psychology Press, 2014. R5. Morgan, George A., et al. IBM SPSS for introductory statistics: Use and interpretation. Routledge, 2012 | |
Evaluation Pattern CIA 70 marks ESE 30 marks | |
CSHO331CSP - PROBABILITY AND RANDOM PROCESS (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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After learning the course for a semester, the student will be aware of the important statistical information for addressing cryptography, error correction and coding, information theory and cryptanalysis. The student would also get a clear idea on some of the cases with their analytical studies in information coding and its related fields. |
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Course Outcome |
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CO1: To define pattern searching algorithms for different applications CO2: To classify vulnerability of subsystem based on the information gathered from different resources CO3: To estimate different optimized process and models CO4: To provide means to find the similarities between the applications and vulnerabilities of the sub-system/system CO5: To analyze about best possible patterns to cluster the possible solutions for different vulnerabilities |
Unit-1 |
Teaching Hours:9 |
Unit 1
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Probability Fundamentals, Bayes’ rule, Markov chains and application to pattern search algorithms, Classical statistical inference, Bayesian statistical inference, Regression techniques | |
Unit-2 |
Teaching Hours:9 |
Unit 2
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Information coding, Pseudorandom number generators, discrete random variables, special distributions and mixed random variables, link and rank analysis , probability bounds, limiting theorem and convergence | |
Unit-3 |
Teaching Hours:9 |
unit 3
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Risk M Basics of statistical learning: models, regression, curse of dimensionality, overfitting, etc. Optimization and convexity, Gradient descent, Newton’s method | |
Unit-4 |
Teaching Hours:9 |
unit 4
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Classification and similarity analysis, linear discriminative analysis, regression analysis, iterative permutation analysis, Support vector machines, nearest neighbor and application of entropy | |
Unit-5 |
Teaching Hours:9 |
unit 5
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Clustering algorithms, graph analysis, pattern detection, Knowledge driven system design, learning with errors, Basics of neural networks | |
Text Books And Reference Books: T1. Gnedenko, Boris V. Theory of probability. Routledge, 2018. T2. Beichelt, Frank. Applied Probability and Stochastic Processes. Chapman and Hall/CRC, 2016. T3. Li, X. Rong. Probability, random signals, and statistics. CRC press, 2017 | |
Essential Reading / Recommended Reading R1. Grimmett, Geoffrey, Geoffrey R. Grimmett, and David Stirzaker. Probability and random processes. Oxford university press, 2001. R2. Papoulis, Athanasios, and S. Unnikrishna Pillai. Probability, random variables, and stochastic processes. Tata McGraw-Hill Education, 2002. R3. Rozanov, Yu. Probability theory, random processes and mathematical statistics. Vol. 344. Springer Science & Business Media, 2012. | |
Evaluation Pattern CIA 70 marks ESE 30 marks | |
CSHO331DAP - STATISTICAL FOUNDATION FOR DATA ANALYTICS (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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● Discuss the core concepts Statistical Analytics and Data manipulation ● Apply the basic principles, models, and algorithms supervised and unsupervised learning mechanisms. ● Analyse the structures and algorithms of regression methods ● Analyse the use of SVM in Data Science Explain notions and theories associated to Convolutional Neural Networks |
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Course Outcome |
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CO 1: Understand and explain concepts associated to Statistical Analytics and Data manipulation. CO 2: Infer details of supervised and unsupervised learning mechanisms. CO 3: Analyse concepts of Convolutional Neural Networks. CO 4: Appraise concepts of Support Vector Machine. CO 5: Solve problems connected to random forest and ensemble learning methods. |
Unit-1 |
Teaching Hours:9 |
STATISTICAL ANALYTICS AND DATA MANIPULATION
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Knowledge discovery: finding structure in data, Data quality versus data quantity, Statistical modeling versus statistical description. Data types, Data summarization, Means, medians, and central tendency, Summarizing variation, Summarizing (bivariate) correlation, Data diagnostics and data transformation, Outlier analysis, Entropy, Data transformation Simple smoothing techniques, Binning, Moving averages, Exponential smoothing. Introduction to SPSS (IBM’s) statistical tool. | |
Unit-2 |
Teaching Hours:9 |
TECHNIQUES FOR SUPERVISED AND UNSUPERVISED LEARNING
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The simple linear model, Multiple inferences and simultaneous confidence bands, Regression diagnostics, Weighted least squares (WLS) regression, Correlation analysis. Unsupervised versus supervised learning, Principal component analysis, Principal components, Implementing a PCA, Exploratory factor analysis. | |
Unit-3 |
Teaching Hours:9 |
NEURAL NETWORKS
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|
Projection Pursuit Regression, Neural Networks, Fitting Neural Network, Some Issues in Training Neural Networks, Bayesian Neural Nets, 0 Computational Considerations. | |
Unit-4 |
Teaching Hours:9 |
SUPPORT VECTOR MACHINES AND FLEXIBLE DISCRIMINANTS
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Introduction, The Support Vector Classifier, Support Vector Machines and Kernels, Generalizing Linear Discriminant Analysis, Flexible Discriminant Analysis, Penalized Discriminant Analysis, Mixture Discriminant Analysis | |
Unit-5 |
Teaching Hours:9 |
RANDOM FORESTS AND ENSEMBLE LEARNING
|
|
Definition of Random Forests, Details of Random Forests- Out of Bag Samples, Variable Importance, Proximity Plots; Analysis of Random Forests; Ensemble Learning, Boosting and Regularization Paths, Learning a Good Ensemble, Rule Ensembles. | |
Text Books And Reference Books: T1. Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media, 2017. T2. Russell, Stuart J., and Peter Norvig. Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited,, 2016. | |
Essential Reading / Recommended Reading R1. Ghahramani, Zoubin. "Probabilistic Machine Learning and Artificial Intelligence." Nature521.7553 (2015): 452. R2. Ian Goodfellow and Yoshua Bengio and Aaron Courville,” Deep Learning ”, MIT Press, March 2018. R3. Wu, James, and Stephen Coggeshall. Foundations of predictive analytics. Chapman and Hall/CRC, 2012. R4. Marcoulides, George A., and Scott L. Hershberger. Multivariate statistical methods: A first course. Psychology Press, 2014. R5. Morgan, George A., et al. IBM SPSS for introductory statistics: Use and interpretation. Routledge, 2012 | |
Evaluation Pattern CIA 70 Marks ESE 30 marks | |
CY321 - CYBER SECURITY (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:0 |
Credits:0 |
Course Objectives/Course Description |
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This mandatory course is aimed at providing a comprehensive overview of the different facets of Cyber Security. In addition, the course will detail into specifics of Cyber Security with Cyber Laws both in Global and Indian Legal environments |
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Course Outcome |
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CO1: Describe the basic security fundamentals and cyber laws and legalities CO2: Describe various cyber security vulnerabilities and threats such as virus, worms, online attacks, Dos and others. CO3: Explain the regulations and acts to prevent cyber-attacks such as Risk assessment and security policy management. CO4: Explain various vulnerability assessment and penetration testing tools. CO5: Explain various protection methods to safeguard from cyber-attacks using technologies like cryptography and Intrusion prevention systems. |
Unit-1 |
Teaching Hours:6 |
UNIT 1
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Security Fundamentals-4 As Architecture Authentication Authorization Accountability, Social Media, Social Networking and Cyber Security.Cyber Laws, IT Act 2000-IT Act 2008-Laws for Cyber-Security, Comprehensive National Cyber-Security Initiative CNCI – Legalities | |
Unit-2 |
Teaching Hours:6 |
UNIT 2
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Cyber Attack and Cyber Services Computer Virus – Computer Worms – Trojan horse.Vulnerabilities - Phishing - Online Attacks – Pharming - Phoarging – Cyber Attacks - Cyber Threats - Zombie- stuxnet - Denial of Service Vulnerabilities - Server Hardening-TCP/IP attack-SYN Flood | |
Unit-3 |
Teaching Hours:6 |
UNIT 3
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Cyber Security Management Risk Management and Assessment - Risk Management Process - Threat Determination Process -Risk Assessment - Risk Management Lifecycle.Security Policy Management - Security Policies - Coverage Matrix Business Continuity Planning - DisasterTypes - Disaster Recovery Plan - Business Continuity Planning Process | |
Unit-4 |
Teaching Hours:6 |
UNIT 4
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Vulnerability - Assessment and Tools: Vulnerability Testing - Penetration Testing Black box- white box.Architectural Integration: Security Zones - Devicesviz Routers, Firewalls, DMZ. Configuration Management - Certification and Accreditation for Cyber-Security. | |
Unit-5 |
Teaching Hours:6 |
UNIT 5
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Authentication and Cryptography: Authentication - Cryptosystems - Certificate Services, Securing Communications: Securing Services - Transport – Wireless - Steganography and NTFS Data Streams. Intrusion Detection and Prevention Systems: Intrusion - Defense in Depth - IDS/IPS -IDS/IPS Weakness and Forensic AnalysisCyber Evolution: Cyber Organization – Cyber Future | |
Text Books And Reference Books: R1. Matt Bishop, “Introduction to Computer Security”, Pearson, 6th impression, ISBN: 978-81-7758-425-7. R2. Thomas R, Justin Peltier, John, “Information Security Fundamentals”, Auerbach Publications. R3. AtulKahate, “Cryptography and Network Security”, 2nd Edition, Tata McGrawHill.2003 R4. Nina Godbole, SunitBelapure, “Cyber Security”, Wiley India 1st Edition 2011 R5. Jennifer L. Bayuk and Jason Healey and Paul Rohmeyer and Marcus Sachs, “Cyber Security Policy Guidebook”, Wiley; 1 edition , 2012 R6. Dan Shoemaker and Wm. Arthur Conklin, “Cyber security: The Essential Body Of Knowledge”, Delmar Cengage Learning; 1 edition, 2011 R7. Stallings, “Cryptography & Network Security - Principles & Practice”, Prentice Hall, 6th Edition 2014 | |
Essential Reading / Recommended Reading NIL | |
Evaluation Pattern Only CIA will be conducted as per the University norms. No ESE Maximum Marks : 50 | |
EC337 - DIGITAL SYSTEMS (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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· To study the fundamentals of digital circuits and concepts used in the analysis and design of various digital systems. |
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Course Outcome |
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CO1: Describe the characteristics of various digital integrated circuit families, logic gates and classify digital circuits based on their construction. L2:Understand CO2: Demonstrate the methods of minimization of complex circuits using Boolean Algebra.L3: Apply CO3: Interpret the methods of Designing combinational circuit.L3: Apply CO4: Illustrate the methods of Designing sequential circuits.L3: Apply CO5: Analyze the digital circuits design using VHDL.L4:Analyze |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
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Switching Theory: Laws of Boolean algebra, Theorems of Boolean algebra, Switching functions, Methods for specification of switching functions - Truth tables and Algebraic forms, Realization of functions using logic gates. Digital Logic Elements: Electronic logic gates, Positive and negative logic, Logic families -TTL, ECL and CMOS, Realization of logic gates. | |
Unit-2 |
Teaching Hours:9 |
BOOLEAN ALGEBRA
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Simplification of Boolean Expressions and Functions: Algebraic methods, Canonical forms of Boolean functions, Minimization of functions using Karnaugh maps, Minimization of functions using Quine-McClusky method. | |
Unit-3 |
Teaching Hours:9 |
COMBINATIONAL CIRCUITS
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Design of Combinational Logic Circuits: Gate level design of Small Scale Integration (SSI) circuits, Modular combinational logic elements - Decoders, Encoders, Priority encoders, Multiplexers and Demultiplexers. Design of Integer Arithmetic Circuits using Combinational Logic: Integer adders - Ripple carry adder and Carry look ahead adder, Integer subtractors using adders, Unsigned integer multipliers - Combinational array circuits, Signed integer multipliers - Booth's coding, Bit-pair recoding, Carry save addition and Wallace tree multiplier, Signed integer division circuits - Combinational array circuits, Complexity and propagation delay analysis of circuits. Design of Combinational Circuits using Programmable Logic Devices (PLDs): Programmable Read Only Memories (PROMs), Programmable Logic Arrays (PLAs), Programmable Array Logic (PAL) devices, Design of multiple output circuits using PLDs. | |
Unit-4 |
Teaching Hours:9 |
SEQUENTIAL CIRCUITS
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Sequential Circuit Elements: Latches -RS latch and JK latch, Flip-flops-RS, JK, T and D flip flops, Master-slave flip flops, Edge-triggered flip-flops. Analysis and Design of Synchronous Sequential Circuits: Models of sequential circuits - Moore machine and Mealy machine, Flip-flops - Characteristic table, Characteristic equation and Excitation table, Analysis of sequential circuits- Flipflop input expressions, Next state equations, Next state maps, State table and State transition diagram, Design of sequential circuits - State transition diagram, State table, Next state maps, Output maps, Expressions for flip-flop inputs and Expressions for circuit outputs, Modular sequential logic circuits- Shift registers, Registers, Counters and Random access memories, Design using programmable logic sequencers (PLSs). Design of Arithmetic Circuits using Sequential Logic : Serial adder for integers, Unsigned integer multiplier, Unsigned integer division circuits, Signed integer division, Floating-pint adder/subtractor - Design of control circuit, Floating - point multiplier. | |
Unit-5 |
Teaching Hours:9 |
CASE STUDY AND INFORMAL LABORATORY
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Case study: Learn the Fundamentals of Digital Logic Design with VHDL Informal Laboratory: · Design and implementation of binary adder / subtractor using basic gates · Design and implementation of applications using multiplexers · Design and implementation of Synchronous & Asynchronous Counters · Design and implementation of Shift Registers Coding Combinational Circuits using Hardware Description Language (HDL) | |
Text Books And Reference Books:
T1 - Donald P Leach, Albert Paul Malvino&GoutamSaha, “Digital Principles and Applications” , Tata McGraw Hill 7th Edition, 2010.
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Essential Reading / Recommended Reading R1 -Stephen Brown. ZvonkoVranesic, “Fundamentals of Digital Logic Design with VHDL”, Tata McGraw Hill, 2nd Edition 2005. R2- R D Sudhaker Samuel, “Illustrative Approach to Logic Design. Sanguine-Pearson”, 2010. R3- Charles H. Roth, “Fundamentals of Logic Design”, Cengage Learning, 5th Edition, 2004. R4- Ronald J. Tocci, Neal S. Widmer. Gregory L. Moss, “Digital Systems Principles and Applications, ” 10th Edition. Pearson Education, 2007 R5- M Morris Mano, “Digital Logic and Computer Design”, Pearson Education, 10th Edition, 2008.
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Evaluation Pattern Assessment is based on the performance of the student throughout the semester. Assessment of each paper · Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks) · End Semester Examination(ESE) : 50% (50 marks out of 100 marks) Components of the CIA CIA I : Mid Semester Examination (Theory) : 25 marks CIA II : Assignments : 10 marks CIA III : Quizzes/Seminar/Case Studies/Project Work : 10 marks Attendance : 05 marks Total : 50 marks For subjects having practical as part of the subject
Assessment of Practical paper Conduct of experiments : 25 marks Observations/Lab Record : 15 marks Viva voce : 10 marks Total : 50 marks (All the above assessments are carried for each experiment during regular lab classes and averaged to max 50 marks at the end of the semester) | |
HS311 - TECHNICAL WRITING (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course Description: Technical Writing Course consists of five units covering; Introduction to Technical Communication, Technical Writing, Soft Skills, Professional Presentation Skills and Professional Etiquettee. It aims to equip the students with the necessary technical communication and writing skills for professional success. Course objectives: This course aims to equip engineering students with effective individual and collaborative technical writing and presentation skills which are necessary to be effective technical communicators in academic and professional contexts. |
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Course Outcome |
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CO1: Understand the basics of technical communication and the use of formal elements of specific genres of documentation CO2: Demonstrate the nuances of technical writing, with reference to English grammar and
vocabulary CO3: Recognize the importance of soft skills and personality development for academic and
professional success. CO4: Understand various techniques involved in oral communication and its application in the
professional contexts. CO5: Realize the importance of having ethical work habits and professional etiquettes. |
Unit-1 |
Teaching Hours:6 |
Introduction to Technical Communication
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Communication Process, Flow, Barriers. Analyzing different kinds of technical documents, Reports/Engineering reports – Types, Importance and Structure of formal reports, information and document design. | |
Unit-2 |
Teaching Hours:6 |
Technical Writing
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Vocabulary for professional writing. Idioms and collocations, Writing drafts and revising, writing style and language. Writing Emails, Resumes, Video resume, Interviews, Types of interviews. | |
Unit-3 |
Teaching Hours:6 |
Soft Skills
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Self development process, Personality development, Types of personality, Perception and attitudes, Emotional intelligence, Time Management, Values and beliefs, Personal goal setting, Creativity, Conflict management, Career planning. | |
Unit-4 |
Teaching Hours:6 |
Professional Presentation Skills
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Writing a speech, Formal presentations, Public speaking, Presentation aids, Group communication, Discussions, Organizational GD, Meetings & Conferences. | |
Unit-5 |
Teaching Hours:6 |
Professional Etiquette
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Email etiquettes, Telephone Etiquettes, Engineering ethics, Role and responsibility of engineer, Work culture in jobs. | |
Text Books And Reference Books: T1: David F. Beer and David McMurrey, Guide to writing as an Engineer, John Willey. New York, 2004 T2: Diane Hacker, Pocket Style Manual, Bedford Publication, New York, 2003. (ISBN 0312406843) T3: Raman Sharma, Technical Communications, Oxford Publication, London, 2004 | |
Essential Reading / Recommended Reading R1. Dale Jungk, Applied Writing for Technicians, McGraw Hill, New York, 2004. (ISBN: 07828357-4) R2. Sharma, R. and Mohan, K. Business Correspondence and Report Writing, TMH New Delhi 2002. R3. Xebec, Presentation Book, TMH New Delhi, 2000. (ISBN 0402213) | |
Evaluation Pattern Evaluation Pattern: CIA 50 Marks ESE 50 Marks CIA 1 Quiz/Assignment/Grammar Test/Oral Talk CIA 2 Mid Semester Exam: MSE CIA 3 Presentation/Mini Project/Portfolio | |
MA334 - DISCRETE MATHEMATICS (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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COURSE DESCRIPTION: This course, Discrete Mathematics (MA334) is offered for three credits in the third semester for the branch of Computer Science Engineering and Information and Technology for different streams. This course develops the logical augmenting and it has topics like Propositional Calculus, Set theory, Group theory, and Coding various Counting techniques. COURSE OBJECTIVE: The objective of the paper is to apply logical reasoning to validate the computer algorithms, to perform the operations associated with sets, functions, relations and groups for the coding and decoding information to check the security of the data. |
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Course Outcome |
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CO1: Distinguish the compound logical statements and validate arguments with logical connectives. [L2] CO2: Solve Lattices and Boolean algebra problems using partial order set . [L3] CO3: Compute coding and decoding problems using group theory and appropriate coding and decoding schemes. [L3] CO4: Classify types of functions/permutation functions as even or odd and solve problems on inverse functions. [L2] CO5: Solve problems related to recurrence using various techniques of counting. [L3] |
Unit-1 |
Teaching Hours:9 |
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Propositional Calculus:
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Propositions – Logical connectives – Compound propositions – Conditional and bi conditional propositions – Truth tables – Tautologies and contradictions – Contrapositive – Logical equivalences and implications – De Morgan’s Laws - Normal forms, Rules of inference – Arguments - Validity of arguments. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Set Theory
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Basic concepts of Sets - Subset – Algebra of sets – The power set – Ordered pairs and Cartesian product – Relations on sets –Types of relations and their properties – Matrix and Graph representation of a relation – Partial ordering – Poset – Hasse diagram – Lattices and their properties – Sublattices – Boolean algebra. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Group Theory and Coding
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Properties – Subgroups - Cosets and Lagrange’s theorem – Normal subgroups – Algebraic system with two binary operations – Preliminaries of Coding - Hamming Metric - group codes: – Basic notions of error correction - Error recovery in group codes. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Counting Techniques-I
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Types of functions - Examples – Composition of functions – Inverse functions – Characteristic function of a set, Mathematical Induction, The Rules of Sum and Product, Permutations, Combinations. | |||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Counting Techniques-II
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Fundamental principles of counting, pigeonhole principle, principle of inclusion and exclusion, Solving Linear Recurrence Relations, Divide-and-Conquer Algorithms and Recurrence Relations, generating functions, Solve Recurrence Relations using Generating Functions. | |||||||||||||||||||||||||||||
Text Books And Reference Books: Text Books T1. Trembly J.P and Manohar R, Discrete Mathematical Structures with Applications to Computer Science, Tata McGrawHill Pub.Co. Ltd, New Delhi, 2003. T2. Ralph. P. Grimaldi, Discrete and Combinatorial Mathematics: An Applied Introduction, Fifth Edition, Pearson Education Asia,Delhi, 2009. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading Reference Books 1. R1. Bernard Kolman, Robert C. Busby, Sharan Cutler Ross, Discrete Mathematical Structures, Fourth Indian reprint, Pearson Education Pvt Ltd., New Delhi, 2003. 2. R2. Kenneth H. Rosen, Discrete Mathematics and its Applications, Fifth Edition, Tata McGraw Hill Pub. Co. Ltd., New Delhi, 2003. 3. R3. Richard Johnsonbaugh, Discrete Mathematics, Fifth Edition,Pearson Education Asia, New Delhi, 2002. | |||||||||||||||||||||||||||||
Evaluation Pattern Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks) End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks Mid Semester Examination (MSE) : Theory Papers:
End Semester Examination (ESE): The ESE is conducted for 100 marks of 3 hours duration. The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution. Question paper pattern is as follows. Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year The criteria for drawing the questions from the Question Bank are as follows 50 % - Medium Level questions 25 % - Simple level questions 25 % - Complex level questions | |||||||||||||||||||||||||||||
VCSE111 - PCAP PROGRAMMING ESSENTIALS IN PYTHON (2022 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:0 |
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Course Objectives/Course Description |
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The PCAP: Programming Essentials in Python course covers all the basics of programming in Python 3, as well as general computer programming concepts and techniques. The course also familiarizes the student with the object-oriented approach. |
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Course Outcome |
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CO1: To familiarize students with general computer programming concepts like conditional execution, functions, loops. CO2: To learn and understand Python programming language syntax, semantics, and the Runtime environment, as well as with general coding techniques and object-oriented programming. |
Unit-1 |
Teaching Hours:30 |
Basics level Python
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Introduction to Python and Computer Programming, Data Types, Variables, Basic, Input-Output Operations, Basic Operators,Boolean Values, Conditional Execution, Loops, Lists and ListProcessing, Logic and BitwiseOperations, Functions, Tuples, Dictionaries, and Data Processing.
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Unit-2 |
Teaching Hours:30 |
Intermediate level Python
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Exceptions, Strings, String and List Methods,Object Oriented Programming in Python,Working with filesystem, Directory trees and Files,Selected Python Standard Library modules (os, date, datetime,calendar). | |
Text Books And Reference Books: https://www.netacad.com/courses/programming/pcap-programming-essentials-python | |
Essential Reading / Recommended Reading https://www.netacad.com/courses/programming/pcap-programming-essentials-python | |
Evaluation Pattern Online Assessment | |
VCSE314 - JAVA PROGRAMMING (2022 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:0 |
Course Objectives/Course Description |
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This course of study builds on the skills gained by students in Java Fundamentals or Java Foundations to help advance Java programming skills. Students will design object-oriented applications with Java and will create Java programs using hands-on, engaging activities. |
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Course Outcome |
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CO1: Utilize java core concepts to solve any real world problems. |
Unit-1 |
Teaching Hours:60 |
Java Programming
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Getting Started with Eclipse, Object and Driver Classes, Data Types and Operators, Strings, Program Structure, Scanner and Conditional Statements, Control Statements, Arrays, Classes, Objects, and Methods - Parameters and Overloading Methods, The Static Modifier and Nested Classes, Inheritance , Polymorphism, Generics, Collections , Sorting and Searching using Collection, String Class, String methods, Regular Expressions, Basics of Input and Output , Input and Output Fundamentals • Deploying an Application, JDBC Introduction. | |
Text Books And Reference Books: https://academy.oracle.com/en/ | |
Essential Reading / Recommended Reading https://academy.oracle.com/en/ | |
Evaluation Pattern Online assessment | |
VCSE315 - RED HAT CERTIFIED SYSTEM ADMINISTRATOR (2022 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:0 |
Course Objectives/Course Description |
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Red Hat System Administration I (RH124) is designed for IT professionals without previous Linux system administration experience. The course provides students with Linux administration competence by focusing on core administration tasks. This course also provides a foundation for students who plan to become full-time Linux system administrators by introducing key command-line concepts and enterprise-level tools. Red Hat System Administration II (RH134) is designed to build the skills to perform the key tasks needed to become a full-time Linux administrator. The course goes deeper into core Linux system administration skills |
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Course Outcome |
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CO1: Students be able to perform essential Linux system administration tasks. Establishing network connectivity, managing physical storage, and basic security administration CO2: Students can perform the key tasks like firewall configuration, troubleshooting etc., needed to become Linux administrators. |
Unit-1 |
Teaching Hours:30 |
Get started with Red Hat Enterprise Linux
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Get started with Red Hat Enterprise LinuxDescribe and define open source, Linux, Linux distributions, and Red Hat Enterprise LinuxAccess the command lineLog into a Linux system and run simple commands using the shell.Manage files from the command lineCopy, move, create, delete, and organize files while working from the bash shell.Get help in Red Hat Enterprise LinuxResolve problems by using local help systems.Create, view, and edit text filesManage text files from command output or in a text editor.Manage local users and groupsCreate, manage, and delete local users and groups, as well as administer local password policies.Control access to filesSet Linux file system permissions on files and interpret the security effects of different permission settings.Monitor and manage Linux processesEvaluate and control processes running on a Red Hat Enterprise Linux system.Control services and daemonsControl and monitor network services and system daemons with the systemd service.Configure and secure SSHConfigure secure command line service on remote systems, using OpenSSH.Analyze and store logsLocate and accurately interpret logs of system events for troubleshooting purposes.Manage networkingConfigure network interfaces and settings on Red Hat Enterprise Linux servers.Install and update software packagesDownload, install, update, and manage software packages from Red Hat and DNF package repositories.Access Linux files systemsAccess, inspect, and use existing file systems on storage attached to a Linux server.Analyze servers and get supportInvestigate and resolve issues in the web-based management interface, getting support from Red Hat to help solve problems.Comprehensive reviewReview the content covered in this course by completing hands-on exercises. | |
Unit-2 |
Teaching Hours:30 |
Improve command line productivity
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Improve command line productivityRun commands more efficiently by using advanced features of the Bash shell, shell scripts, and various utilities provided by Red Hat Enterprise Linux.Schedule future tasksSchedule commands to run in the future, either one time or on a repeating schedule.Analyze and Store LogsLocate and accurately interpret system event logs for troubleshooting purposes.Archive and Transfer FilesArchive and copy files from one system to another.Tune system performanceImprove system performance by setting tuning parameters and adjusting scheduling priority of processes.Manage SELinux securityProtect and manage the security of a server by using SELinux.Manage logical volumesCreate and manage logical volumes containing file systems and swap spaces from the command line.Access network-attached storageUse the NFS protocol to administer network-attached storage.Control the boot processManage the boot process to control services offered and to troubleshoot and repair problems.Manage network securityControl network connections to services using the system firewall and SELinux rules.Install Red Hat Enterprise LinuxInstall Red Hat Enterprise Linux on servers and virtual machines.Run ContainersObtain, run, and manage simple, lightweight services as containers on a single Red Hat Enterprise Linux server. | |
Text Books And Reference Books: Redhat Couse Meterials | |
Essential Reading / Recommended Reading Redhat Couse Meterials | |
Evaluation Pattern CIA | |
BS451 - BIOLOGY FOR ENGINEERS LABORATORY (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:1 |
Course Objectives/Course Description |
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To train students in applications of biology in the engineering domain. The course will deal with problems specific to the circuit branches |
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Course Outcome |
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CO1: To measure biological signals CO2: To implement signal processing in the biomedical instrument CO3: To test the imaging technique CO4: To integrate and test an air quality test instrument |
Unit-1 |
Teaching Hours:30 |
Biology for Engineers Laboratory
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1. Experiment on biological sensors and their characteristics. 2. Development of a biomedical instrument using sensors and signal processors. 6 3. Imaging technology for biological signals. 4. Integration and testing of the biomedical instrumentation systems. 5. Measurement of air quality. | |
Text Books And Reference Books: T1. Benny Joseph, ‘Environmental Science and Engineering’, Tata McGraw-Hill, New Delhi, 2006. T2. Gilbert M. Masters, ‘Introduction to Environmental Engineering and Science’, 2nd edition, Pearson Education, 2004. | |
Essential Reading / Recommended Reading R1: Dharmendra S. Sengar, ‘Environmental law’, Prentice hall of India Pvt Ltd, New Delhi, 2007. R2.ErachBharucha, “Textbook of Environmental Studies”, Universities Press(I) Pvt, Ltd, Hydrabad, 2015. R3. G. Tyler Miller and Scott E. Spoolman, “Environmental Science”, Cengage | |
Evaluation Pattern CIA : 50 Marks ESE : 50 Marks
| |
CS432P - OPERATING SYSTEMS (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Outcome |
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CO1: Demonstrate the Structure, Components and its basic functionalities of Operating System CO2: Distinguish various process management principles for given problem using appropriate tool CO3: Elucidate the process synchronization mechanisms, deadlock environment and its solutions in the given processes
CO4: Inspect various memory management strategies for the given problems in memory systems CO5: Build file structure to distribute the same across the memory.
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Unit-1 |
Teaching Hours:9 |
INTRODUCTION
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Introduction : What operating systems do, Computer System Architecture, Operating System Structure, Operating System Operations, Process Management, Memory Management, Storage Management, Protection and Security; System Structures: Operating System Services, User Operating System Interface, System Calls, Types of System Calls. | |
Unit-2 |
Teaching Hours:9 |
PROCESS MANAGEMENT
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Process Management: Process Concept, Process Scheduling, Operations on Processes, Inter-process Communication; Threads: Overview, Multithreading Models, Thread Libraries; CPU Scheduling: Basic Concepts, Scheduling Criteria, Scheduling Algorithms, Multiple- Processor Scheduling | |
Unit-3 |
Teaching Hours:9 |
PROCESS SYNCHRONIZATION AND DEADLOCKS
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Process Synchronization: Background, The Critical Section Problem, Peterson’s Solution, Synchronization Hardware, Semaphores, Classical Problems of Synchronization, Monitors, Synchronization Examples, Deadlocks | |
Unit-4 |
Teaching Hours:9 |
MEMORY MANAGEMENT AND VIRTUAL MEMORY
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Memory Management: Background, Swapping, Contiguous Memory Allocation, Paging.
Virtual Memory : Background, Demand Paging, Copy on Write, Page Replacement, Allocation of frames, Thrashing, Allocating Kernel Memory | |
Unit-5 |
Teaching Hours:9 |
FILE SYSTEM INTERFACE AND FILE SYSTEM IMPLEMENTATION & MASS STORAGE STRUCTURE
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File System Interface: File System: File Concept, Access Methods, Directory Structure, File System Mounting, File Sharing, Protection.
File System Implementation & Mass Storage Structure: Implementing File Systems: File System Structure, File System Implementation, Directory Implementation, Allocation Methods, Free Space Management. Disk structure, Disk Attachment, Disk Scheduling Methods, Disk Management, Swap-Space Management | |
Text Books And Reference Books: 1. Abraham Silberschatz, , Peter Baer Galvin and Greg Gagne “Operating System Concepts”, John Wiley & Sons (ASIA) Pvt. Ltd,Tenth Edition ,2018. 2. Harvey M. Deitel, “Operating Systems”, Pearson Education Pvt. Ltd, Third Edition, 2008. | |
Essential Reading / Recommended Reading R1. Andrew S. Tanenbaum, “Modern Operating Systems”, Prentice Hall of India Pvt. Ltd, Fourth Edition 2016. R2. William Stallings, “Operating System- Internals and Design Principles”, Pearson Education, Nineth Edition, 2018. R3. Pramod Chandra P. Bhatt – “An Introduction to Operating Systems, Concepts and Practice”, PHI, Fifth Edition, 2019. | |
Evaluation Pattern CIA 70 marks ESE 30 Marks | |
CS433P - PROGRAMMING PARADIGM (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Software development in business environment has become more sophisticated, the software implementation is becoming increasingly complex and requires the best programming paradigm which helps to eliminate complexity of large projects. Object Oriented Programming (OOP) has become the predominant technique for writing software at present. Many other important software development techniques are based upon the fundamental ideas captured by object-oriented programming. The course also caters to the understanding of event driven programming, generic programming and concurrent programming. |
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Course Outcome |
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CO 1: Demonstrate the fundamental concepts of Object-Oriented Programming. CO 2: Make use of the inheritance and interface concepts for effective code reuse. CO 3: Develop dynamic and interactive graphical applications using AWT and SWING CO 4: Examine the generic programming and exception handling concepts.
CO 5: Interpret the importance of multi-threading concepts to develop concurrent applications. |
Unit-1 |
Teaching Hours:9 |
OBJECT-ORIENTED PROGRAMMING ? FUNDAMENTALS
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Review of OOP - Objects and classes in Java – defining classes – methods - access specifiers – static members – constructors – finalize method – Arrays – Strings - Packages – JavaDoc comments. | |
Unit-2 |
Teaching Hours:9 |
OBJECT-ORIENTED PROGRAMMING ? INHERITANCE
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Inheritance – class hierarchy – polymorphism – dynamic binding – final keyword – abstract classes – the Object class – Reflection – interfaces – object cloning – inner classes | |
Unit-3 |
Teaching Hours:9 |
EVENT-DRIVEN PROGRAMMING
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Graphics programming – Frame – Components – working with 2D shapes – Using color, fonts, and images - Basics of event handling – event handlers – adapter classes – actions – mouse events – AWT event hierarchy – introduction to Swing – Model-View- Controller design pattern – buttons – layout management – Swing Components | |
Unit-4 |
Teaching Hours:9 |
GENERIC PROGRAMMING
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Motivation for generic programming – generic classes – generic methods – generic code and virtual machine – inheritance and generics – reflection and generics – exceptions – exception hierarchy – throwing and catching exceptions. | |
Unit-5 |
Teaching Hours:9 |
CONCURRENT PROGRAMMING
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Multi-threaded programming – interrupting threads – thread states – thread properties – thread synchronization – thread-safe Collections – Executors – synchronizers – threads and event-driven programming, Parallel programming –fork, join framework. | |
Text Books And Reference Books: T1. Cay S. Horstmann and Gary Cornell, “Core Java, Volume I – Fundamentals”, Eleventh Edition, Prentice Hall, 2018. | |
Essential Reading / Recommended Reading
R1. Herbert Schildt, “Java: The Complete Reference (Complete Reference Series)”, Eleventh Edition, 2020. R2. Cay S. Horstmann , “Java SE8 for the Really Impatient: A Short Course on the Basics (Java Series)”, 2014. R3. Bruce Eckel, “Thinking in Java”, 4th Edition, Prentice Hall Professional, 2006. R4. Doug Rosenberg and Matt Stephens, “Use Case Driven Object Modeling with UML: Theory and Practice (Expert's Voice in UML Modeling)”,APress, 2013.
R5.Martina Seidl, Marion Scholz, Christian Huemer and GertiKappel , “UML @ Classroom An Introduction to Object-Oriented Modeling Series: Undergraduate Topics in Computer Science”, Springer, 2015 | |
Evaluation Pattern CIA - 70 Marks ESE - 30 Marks | |
CS434 - FORMAL LANGUAGE AND AUTOMATA THEORY (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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1. To have an understanding of finite state and pushdown automata. 2. To have a knowledge of regular languages and context free languages. 3. To know the relation between regular language, context free language and corresponding recognizers. 4. To study the Turing machine and classes of problems. |
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Course Outcome |
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CO1: Design finite automata with conversion between types of finite automata. CO2: Develop regular expression and minimize the given finite automata for any regular language. CO3: Develop context free grammar, parse trees and pushdown automata for a given context free language. CO4: Experiment with CFLs and design of Turing machine for a given language. CO5: Explain decidable and undecidable problems, solvable and unsolvable problems with their complexity analysis. |
Unit-1 |
Teaching Hours:9 |
AUTOMATA
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Automata - Introduction to formal proof – Additional forms of proof – Inductive proofs –Finite Automata (FA) – Central concepts of Automata Theory, Representation of Automata, Deterministic Finite Automata (DFA) – Non-deterministic Finite Automata (NFA) – Finite Automata with Epsilon transitions. Introduction to automata simulation tools | |
Unit-2 |
Teaching Hours:9 |
REGULAR EXPRESSIONS AND LANGUAGES
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Regular Expressions and Languages
Regular Expression – FA and Regular Expressions – Proving languages not to be regular – Closure properties of regular languages – Equivalence and minimization of Automata. | |
Unit-3 |
Teaching Hours:9 |
CONTEXT-FREE GRAMMAR AND LANGUAGES
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Context-Free Grammar and Languages
Context-Free Grammar (CFG) – LMD, RMD, Parse Trees – Ambiguity in grammars and languages – Definition of the Pushdown automata – Languages of a Pushdown Automata, Designing of a PDA and string acceptance – Equivalence of Pushdown automata and CFG, Non-Deterministic Pushdown Automata. | |
Unit-4 |
Teaching Hours:9 |
PROPERTIES OF CONTEXT-FREE LANGUAGES
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Properties of Context-Free Languages
Simplifications of CFG, Normal forms for CFG – Pumping Lemma for CFL - Closure Properties of CFL – Turing Machines – Definition, Problems, Language accepted, String acceptance, Programming Techniques for TM. | |
Unit-5 |
Teaching Hours:9 |
UNDECIDABILITY
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Undecidability
A language that is not Recursively Enumerable (RE) – An undecidable problem that is RE – Undecidable problems about Turing Machine – Post’s Correspondence Problem - The classes P and NP, Linear Bounded Automata - Definition and examples | |
Text Books And Reference Books: 1. J.E.Hopcroft, R.Motwani and J.D Ullman, “Introduction to Automata Theory, Languages and Computations”, Pearson Education, 2008.
2. Peter Linz “An Introduction to formal languages and automata”, sixth edition, Jones and Bartlett Learning, 2016. | |
Essential Reading / Recommended Reading 1. H.R.Lewis and C.H.Papadimitriou, “Elements of The theory of Computation”, Second Edition, Pearson Education/PHI, 2003. 2. J.Martin, “Introduction to Languages and the Theory of Computation”, 3rd Edition, TMH, 2003. 3. MichealSipser, “Introduction of the Theory and Computation”, Thomson Brokecole, 3rd Edition, 1997 | |
Evaluation Pattern Contnuous Internal Assessment - 50 Marks End Semester Exam - 50 Marks | |
CS435P - COMPUTER ORGANIZATION AND ARCHITECTURE (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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This course will help the students to learn about basic structure of computer system, design of arithmetic and logic unit with the implementation of fixed and floating point numbers. Further, it will give knowledge about design of control unit and pipelined processing concepts. It discusses about various parallel processing architectures, different memory systems and I/O Communication systems |
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Course Outcome |
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CO1: Demonstrate the functions of basic components of computer system and Instruction set Architecture CO2: Select suitable arithmetic algorithm to solve given arithmetic and logical problems
CO3: Utilize appropriate instruction level parallelism concepts in multiprocessing environment CO4: Identify suitable control unit design and pipelining principles in computer architecture design CO5: Choose suitable memory and I/O system design |
Unit-1 |
Teaching Hours:9 |
FUNDAMENTALS OF COMPUTER SYSTEM
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Functional Units – Basic Operational Concepts – Performance – Instructions: Language of the Computer – Operations, Operands – Instruction representation – Logical operations – decision making – MIPS Addressing. | |
Unit-2 |
Teaching Hours:9 |
COMPUTER ARTHIMETIC
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Addition and Subtraction – Multiplication – Division – Floating Point Representation – Floating Point Operations – Subword Parallelism | |
Unit-3 |
Teaching Hours:9 |
BASIC PROCESSING AND CONTROL UNIT
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A Basic MIPS implementation – Building a Datapath – Control Implementation Scheme – Pipelining – Pipelined data path and control – Handling Data Hazards & Control Hazards – Exceptions. | |
Unit-4 |
Teaching Hours:9 |
PARALLELISM
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Parallel processing challenges – Flynn‘s classification – SISD, MIMD, SIMD, SPMD, and Vector Architectures - Hardware multithreading – Multi-core processors and other Shared Memory Multiprocessors - Introduction to Graphics Processing Units, Clusters, Warehouse Scale Computers and other Message-Passing Multiprocessors. | |
Unit-5 |
Teaching Hours:9 |
MEMORY AND I/O
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Memory Hierarchy - memory technologies – cache memory – measuring and improving cache performance – virtual memory, TLB‘s – Accessing I/O Devices – Interrupts – Direct Memory Access – Bus structure – Bus operation – Arbitration – Interface circuits - USB. | |
Text Books And Reference Books: Text Books: T1. David A. Patterson and John L. Hennessy, “Computer Organization and Design: The Hardware/Software Interface”, Fifth Edition, Morgan Kaufmann / Elsevier, 2014. T2. Carl Hamacher, ZvonkoVranesic, SafwatZaky and NaraigManjikian, “Computer Organization and Embedded Systems”, Sixth Edition, Tata McGraw Hill, 2012. | |
Essential Reading / Recommended Reading Reference Books: R1. William Stallings, “Computer Organization and Architecture – Designing for Performance”, Sixth Edition, Pearson Education, 2003. R2. John L. Hennessey and David A. Patterson, “Computer Architecture –A Quantitative Approach”, Fifth Edition, Morgan Kaufmann / Elsevier Publishers,2012. | |
Evaluation Pattern CIA - 70% out of 100 ESE - 30% out of 100 | |
CSHO432AIP - ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Description: This course offers a solid foundation of key ideas in machine learning. The objective is to impart expertise on using Python packages related to Machine Learning and supervised and unsupervised techniques.
Course Objective: 1. To gain knowledge in the basics of Python Machine Learning Libraries. 2. To analyze the applicability, benefits, and drawbacks of the Supervised and Unsupervised machine learning techniques. 3. To acquire knowledge on the recommendation systems and their working methodology |
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Course Outcome |
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CO1: Explain Forms of Learning and demonstrate the fundamental machine learning operations in Python. CO2: Examine different machine learning regression techniques. CO3: Analyze supervised classification methods. CO4: Inspect various unsupervised clustering techniques. CO5: Outline the concept of recommendation systems for real-time problems. |
Unit-1 |
Teaching Hours:9 |
Unit 1 Learning
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Artificial Intelligence - Introduction to Artificial Intelligence, Machine Learning, Deep Learning, Applications of Artificial Intelligence, Learning Agent. Forms of Learning - Supervised Learning, Unsupervised Learning, Semi supervised Learning, Reinforcement Learning Python libraries suitable for Machine Learning - Numpy, Pandas, Data visualization using matplotlib, sklearn. | |
Unit-2 |
Teaching Hours:9 |
Unit 2 Supervised Learning - Regression
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Linear and Non Linear regression -Simple Linear regression,Multiple Linear Regression - Multivariate Linear regression -Model Evaluation Methods(Loss Function, the cost function, Residual Errors and Mean Square Error(MSE))-Applications of Regression. | |
Unit-3 |
Teaching Hours:9 |
Unit 3 Supervised Learning - Classification
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K-Nearest Neighbors - Decision Tree - Support Vector Machines -Logistic RegressionClassification Metrics (Confusion Matrix, Accuracy, Precision Recall (Sensitivity), F1 Score, Area Under the Curve-Receiver Operator Characteristic (AUC-ROC))-Applications of classification
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Unit-4 |
Teaching Hours:9 |
Unit 4 UnSupervised Learning - Clustering
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K-means clustering - Hierarchical clustering, Agglomerative Hierarchical clustering,Types of linkage - Density-Based Clustering,DBSCAN-Applications of Clustering
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Unit-5 |
Teaching Hours:9 |
Unit 5 Recommender Systems
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Recommendation System,Content-based filtering,Collaborative filtering,Hybrid - Real time case studies on Recommender Systems.
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Text Books And Reference Books: T1. Andreas C. Müller, Sarah Guido , “Introduction to Machine Learning with Python”,O'Reilly Media, Inc.,First Edition, September 2016,ISBN: 9781449369897. T2. Sebastian Raschka, Vahid Mirjalili, “Python Machine Learning - Third Edition”, O'Reilly Media, Inc.,Third Edition, December 2019, ISBN: 9781789955750. | |
Essential Reading / Recommended Reading R1. Manaranjan Pradhan, U. Dinesh Kumar, “ Machine Learning Using Python”, Wiley india Pvt. Ltd, 2019 Edition, ISBN: 9788126579907. R2. Wes McKinney, ”Python for Data: Data Wrangling with Pandas, NumPy, and IPython”, Second Edition,O′Reilly, 2017. R3. John Paul Mueller, Luca Massaron, “Machine Learning For Dummies”, John Wiley & Sons, Inc., 2016. R4. Tom M. Mitchell, Machine Learning, McGraw-Hill Education (India) Private Limited, 2013. R5. Kevin Murphy, Machine Learning: A Probabilistic Perspective, MIT Press, 2012. | |
Evaluation Pattern CIA: 50 ESE: 50 | |
CSHO432CSP - MOBILE AND NETWORK BASED ETHICAL HACKING (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Description: This course includes introductory concepts of computer networks scanning , hacking techniques, mobile hacking techniques, firewall techniques, and few case studies on various hacking scenarios.
Course Objective: Teaching the phases of ethical hacking using various open source tools available for ethical hacking process like penetration testing ,information gathering, password cracking,and vulnerability assessment. |
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Course Outcome |
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CO1: To describe the vulnerability scanning for networks. CO2: To understand the information-gathering modes for any attack on the network. CO3: To demonstrate different hacking processes and corresponding attacks for mobile platforms.
CO4: To interpret means to evade firewalls and other security parameters for ethical hacking.
CO5: To apply various possible tools for different vulnerabilities that are exploited for hacking. |
Unit-1 |
Teaching Hours:9 |
Unit 1
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Introduction to ethical hacking, IP addressing, Network routing protocols, network security, network scanning, vulnerability assessment OpenVAS, Nessus, etc. of computation device (Mobile, PC, etc.) and system network.
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Unit-2 |
Teaching Hours:9 |
Unit 2
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Computation system hacking, modes of gathering information, password cracking, penetration testing including backdoor issues, Malware threats, and different cyber-related attacks. | |
Unit-3 |
Teaching Hours:9 |
Unit 3
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Introduction to Mobile Hacking, encryption types and attacks, different mobile platforms, and corresponding vulnerabilities.
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Unit-4 |
Teaching Hours:9 |
Unit 4
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Evading firewalls, standard detection systems and frameworks, and other possible attack detection methods.
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Unit-5 |
Teaching Hours:9 |
Unit 5
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Case studies: various hacking scenarios, information gathering, and possible solutions.
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Text Books And Reference Books: T1. McNab, Chris. Network security assessment: know your network. " O'Reilly Media, Inc.", 2007. T2. Weidman, Georgia. Penetration testing: a hands-on introduction to hacking. No Starch Press, 2014. T3. Engebretson, Patrick. The basics of hacking and penetration testing: ethical hacking and penetration testing made easy. Elsevier, 2013. T4. Dwivedi, Himanshu. Mobile application security. Tata McGraw-Hill Education, 2010.
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Essential Reading / Recommended Reading https://nmap.org- Open Source Network Scanning tool. https://www.openvas.org open source tool, network vulnerability scanner Hacking: The Art of Exploitation Metasploit: The Penetration Tester's Guide Metasploit, Nessus, Recon-ng, Better cap, Ettercap, Open-Vas, Burp-suit, Hydra, Medusa, Air crack-ng. | |
Evaluation Pattern CIA-50 ESE-50 | |
CSHO432DAP - BIG DATA ANALYTICS (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Description: This course gives an overview of Big Data Analytics and it can be described as the acts of studying data to observe patterns and to draw a conclusion to make an important decision. In addition, it also focuses on the big data technologies and tools such as Hadoop, Hive, HBase, and Pig that are available for storage, retrieval, and processing of big data. It helps a student to perform a variety of real-time analytics and processing of different data sets on different domains.
Course Objective: 1. To know the fundamental concepts of big data and analytics. 2. To explore tools and practices for working with big data. 3. To examine large amounts of data to uncover hidden patterns, correlations and other insights to help make data-informed decisions. |
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Course Outcome |
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CO1: Demonstrate the big data and its use cases from selected business domains. CO2: Experiment with NoSQL data management for creating database for various applications.
CO3: Make use of Hadoop distributed file system for developing big data applications. CO4: Develop MapReduce applications for improving parallel processing in real-time applications.
CO5: Examine various Hadoop related tools such as Hbase, Cassandra, Pig and Hive for big data analytics.
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Unit-1 |
Teaching Hours:9 |
Unit 1 UNDERSTANDING BIG DATA
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What is big data – why big data –.Data!, Data Storage and Analysis, Comparison with Other Systems, Rational Database Management System , Grid Computing, Volunteer Computing, convergence of key trends – unstructured data – industry examples of big data – web analytics – big data and marketing – fraud and big data – risk and big data – credit risk management – big data and algorithmic trading – big data and healthcare – big data in medicine – advertising and big data– big data technologies – introduction to Hadoop – open source technologies – cloud and big data – mobile business intelligence – Crowd sourcing analytics – inter and trans firewall analytics. | |
Unit-2 |
Teaching Hours:9 |
Unit 2 NOSQL DATA MANAGEMENT
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Introduction to NoSQL – aggregate data models – aggregates – key-value and document data models – relationships –graph databases – schema less databases – materialized views – distribution models – sharding – version – Map reduce –partitioning and combining – composing map-reduce calculations. | |
Unit-3 |
Teaching Hours:9 |
Unit 3 BASICS OF HADOOP
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Data format – analysing data with Hadoop – scaling out – Hadoop streaming – Hadoop pipes – design of Hadoop distributed file system (HDFS) – HDFS concepts – Java interface – data flow – Hadoop I/O – data integrity – compression – serialization – Avro – file-based data structures. | |
Unit-4 |
Teaching Hours:9 |
Unit 4 MAPREDUCE APPLICATIONS
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MapReduce workflows – unit tests with MRUnit – test data and local tests – anatomy of MapReduce job run – classic Map-reduce – YARN – failures in classic Map-reduce and YARN – job scheduling – shuffle and sort – task execution –MapReduce types – input formats – output formats. | |
Unit-5 |
Teaching Hours:9 |
Unit 5 HADOOP RELATED TOOLS
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Hbase – data model and implementations – Hbase clients – Hbase examples –praxis. Cassandra – Cassandra data model –Cassandra examples – Cassandra clients –Hadoop integration. Pig – Grunt – pig data model – Pig Latin – developing and testing Pig Latin scripts. Hive – data types and file formats – HiveQL data definition – HiveQL data manipulation –HiveQL queries-case study. | |
Text Books And Reference Books: T1. Tom White, "Hadoop: The Definitive Guide", 4th Edition, O'Reilley, 2012. T2. Eric Sammer, "Hadoop Operations",1st Edition, O'Reilley, 2012. T3. Nataraj Dasgupta, "Practical Big Data Analytics", Packt Publishing Ltd., 2018. ISBN 978-1-78355-439-3 T4. Arshdeep Bahga & Vijay Madisetti, "Big Data Science & Analytics: A Hands-On Approach", Published by Vijay Madisetti, 2016. ISBN: 978-1-949978-00-1 | |
Essential Reading / Recommended Reading Reference Books: R1. VigneshPrajapati, Big data analytics with R and Hadoop, SPD 2013. R2. Lars George, "HBase: The Definitive Guide", O'Reilley, 2011. R3. Alan Gates, "Programming Pig", O'Reilley, 2011. R4. E. Capriolo, D. Wampler, and J. Rutherglen, "Programming Hive", O'Reilley, 2012. | |
Evaluation Pattern CIA - 50% ESE - 30% | |
EVS421 - ENVIRONMENTAL SCIENCE (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:0 |
Credits:0 |
Course Objectives/Course Description |
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To understand the scope and importance of environmental science towards developing a conscious community for environmental issues, both at global and local scale. |
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Course Outcome |
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CO1: Explain the components and concept of various ecosystems in the environment (L2, PO7) CO2: Explain the necessity of natural resources management (L2, PO1, PO2 and PO7)
CO3: Relate the causes and impacts of environmental pollution (L4, PO1, PO2, and PO3, PO4)
CO4: Relate climate change/global atmospheric changes and adaptation (L4,PO7)
CO5: Appraise the role of technology and institutional mechanisms for environmental protection (L5, PO8) |
Unit-1 |
Teaching Hours:6 |
Introduction
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Environment and Eco systems – Definition, Scope and importance. Components of environment. Concept and Structure of eco systems. Material Cycles – Nitrogen, Carbon, Sulphur, Phosphorous, Oxygen. Energy Flow and classification of Eco systems. | |
Unit-2 |
Teaching Hours:6 |
Natural Resources
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Classification and importance- Forest, Water, Mineral, Food, Energy. Management of natural resources – challenges and methods. Sustainable development – Goals, Agriculture, Industries | |
Unit-3 |
Teaching Hours:6 |
Environmental Pollution
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Causes and Impacts – Air pollution, Water pollution, Soil Pollution, Noise Pollution, Marine Pollution, Municipal Solid Wastes, Bio Medical and E-Waste. Solid Waste Management | |
Unit-4 |
Teaching Hours:6 |
Climate change/Global Atmospheric Change
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Global Temperature, Greenhouse effect, global energy balance, Global warming potential, International Panel for Climate Change (IPCC) Emission scenarios, Oceans and climate change. Adaptation methods. Green Climate fund. Climate change related planning- small islands and coastal region. Impact on women, children, youths and marginalized communities | |
Unit-5 |
Teaching Hours:6 |
Environmental Protection
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Technology, Modern Tools – GIS and Remote Sensing,. Institutional Mechanisms - Environmental Acts and Regulations, Role of government, Legal aspects. Role of Nongovernmental Organizations (NGOs) , Environmental Education and Entrepreneurship | |
Text Books And Reference Books: T1Kaushik A and Kaushik. C. P, “Perspectives in Environmental Studies”New Age International Publishers, New Delhi, 2018 [Unit: I, II, III and IV] T2Asthana and Asthana, “A text Book of Environmental Studies”, S. Chand, New Delhi, Revised Edition, 2010 [Unit: I, II, III and V] T3Nandini. N, Sunitha. N and Tandon. S, “environmental Studies” , Sapana, Bangalore, June 2019 [Unit: I, II, III and IV] T4R Rajagopalan, “Environmental Studies – From Crisis to Cure”, Oxford, Seventh University Press, 2017, [Unit: I, II, III and IV]
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Essential Reading / Recommended Reading R1.Miller. G. T and Spoolman. S. E, “Environmental Science”, CENAGE Learning, New Delhi, 2015 R2.Masters, G andEla, W.P (2015), Introduction to environmental Engineering and Science, 3rd Edition. Pearson., New Delhi, 2013. R3.Raman Sivakumar, “Principals of Environmental Science and Engineering”, Second Edition, Cengage learning Singapore, 2005. R4.P. Meenakshi, “Elements of Environmental Science and Engineering”, Prentice Hall of India Private Limited, New Delhi, 2006. R5.S.M. Prakash, “Environmental Studies”, Elite Publishers Mangalore, 2007 R6.ErachBharucha, “Textbook of Environmental Studies”, for UGC, University press, 2005. R7. Dr. Pratiba Sing, Dr. AnoopSingh and Dr. PiyushMalaviya, “Textbook of Environmental and Ecology”, Acme Learning Pvt. Ltd. New Delhi. | |
Evaluation Pattern No Evaluation | |
HS422 - PROFESSIONAL ETHICS (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Understand the importance of Values and Ethics in their personal lives and professional careers |
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Course Outcome |
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CO1: Understand the importance of Values and Ethics in their personal lives and professional careers CO2: Learn the rights and responsibilities as an employee, team member and a global citizen CO3: Estimate the impact of self and organization?s actions on the stakeholders and society CO4: Develop an ethical behaviour under all situations CO5: Appreciate the significance of Intellectual Property as a very important driver of growth and development in today?s world and be able to statutorily acquire and use different types of intellectual property in their professional life |
Unit-1 |
Teaching Hours:6 |
Introduction to Ethics
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Introduction to Professional Ethics : Definition, Nature, Scope- Moral Dilemmas- moral Autonomy-Kohlberg’s theory- Gilligan’s theory, Profession Persuasive, Definitions, Multiple motives, Models of professional goals. Moral Reasoning and Ethical theories – Professional Ideals and Virtues- Theories of Right Action, Self- interest, Customs and Regions- Use of ethical Theories | |
Unit-2 |
Teaching Hours:6 |
Engineering as Social Experimentation and Responsibility
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Engineering as Social Experimentation and Responsibility For Safety Engineering as experimentation- Engineers as responsible experimenters, the challenger case, Codes of Ethics, A balanced outlook on law. Concept of safety and risk, assessment of safety and risk- risk benefit analysis and reducing the risk- three- mile island, Chernobyl and safe exists. | |
Unit-3 |
Teaching Hours:6 |
Global Issues and Introduction To Intellectual Property
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Global Issues and Introduction To Intellectual Property - Multinational corporations- Environmental ethics- Computer ethics and Weapons developments. Meaning and Types of Intellectual Property, Intellectual Property. Law Basics, Agencies responsible for intellectual property registration, International Organizations, Agencies and Treaties, Importance of Intellectual Property Rights. | |
Unit-4 |
Teaching Hours:6 |
Foundations of Trademarks
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Foundations of Trademarks - Meaning of Trademarks, Purpose and Functions of Trademarks, types of Marks, Acquisition of Trademark rights, Common Law rights, Categories of Marks, Trade names and Business Name, Protectable Matter, Exclusions from Trademark Protection. | |
Unit-5 |
Teaching Hours:6 |
Foundations of Copyrights Law
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Foundations of Copyrights Law - Meaning of Copyrights, Common Law rights and Rights under the 1976 copyright Act, Recent developments of the Copyright Act, The United States Copyright Office | |
Text Books And Reference Books: T1. Mike Martin and Roland Schinzinger, “Ethics in Engineering”, McGraw-Hill, New York 1996. T2. Govindarajan M, Natarajan S, Senthil Kumar V. S, “Engineering Ethics”, Prentice Hall of India, New Delhi, 2004.
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Essential Reading / Recommended Reading R1. Jayashree Suresh &B.S.Raghavan “Human values and Professional Ethics”, S. Chand, 2009.
R2. Govindarajan, Natarajan and Senthilkumar “Engineering Ethics”, PHI:009.
R3. Nagarajan “A Text Book on Professional ethics and Human values”, New Age International, 2009.
R4. Charles &Fleddermann “Engineering Ethics”, Pearson, 2009.
R5. Rachana Singh Puri and Arvind Viswanathan, I.K.”Practical Approach to Intellectual Property rights”, International Publishing House, New Delhi. 2010.
R6. A.B.Rao “Business Ethics and Professional Values”, Excel, 2009 | |
Evaluation Pattern CIA I -Evaluated out of (20) --> CIA I cnverted to (10) CIA II - Evaluated out of (50) ---> CIA II cnverted to ( 25) CIA III - Evaluated out of (20) ----> CIA III cnverted to (10) Total CIA is scaled down to 20 Att. Marks5 ESE Evaluated out of (50) ---> ESE converted to (25) Total marks - 50 | |
MA431 - PROBABILITY AND QUEUING THEORY (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course Description: This course, Probability and Queuing Theory is offered for three credits in the fourth semester for the various streams of Computer Science Engineering and Electronics and Communication Engineering. It describes the fundamentals and advanced concepts of Probability and Random Variable, Standard Distributions, Two Dimensional Random Variables, Random Processes and Markov Chains and Queuing Theory. Course objectives: To describe the fundamentals and advanced concepts of probability theory, random process, queuing theory to support the graduate coursework and research. |
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Course Outcome |
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CO1: Differentiate the continuous and discrete probability distributions and estimate the probability for the different parameter for the data. {L2} {PO1, PO2, PO3} CO2: Distinguish different standard distributions like Binomial, Poisson, Uniform, and Normal, gamma, Weibull etc. and able to estimate the probability with proper examples. {L4} {PO1, PO2, PO3} CO3: Interpret the data with the aid of Covariance Correlation and regression for two-dimensional random variable. {L3} {PO1, PO2, PO3} CO4: Classify different random processes such as Stationary process, Markov process, Poisson process, Birth and death process, Markov chains, and explain transition probabilities - limiting distributions with examples. {L4} {PO1, PO2, PO3} CO5: Construct the different Queuing models to find the number of customers in the system, waiting time etc. {L3} {PO1, PO2, PO3} |
Unit-1 |
Teaching Hours:9 |
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Probability and Random Variable
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Axioms of probability - Conditional probability, Random variable - Probability mass function - Probability density function - Properties. Mathematical Expectation and Moments Relation between central and Non-central moments. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Standard Distributions
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Binomial, Poisson, Geometric, Negative Binomial, Uniform, Exponential, Gamma, Weibull and Normal distributions and their properties-Functions of a random variable. Moment generating functions and their properties. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Two Dimensional Random Variables
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Joint distributions - Marginal and conditional distributions – Covariance –Correlation and regression - Transformation of random variables – Central limit theorem. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Random Processes and Markov Chains
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Classification - Stationary process - Markov process - Poisson process - Birth and death process - Markov chains - Transition probabilities - Limiting distributions. Transition Diagram. | |||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Queuing Theory
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Markovian models – M/M/1, M/M/C , finite and infinite capacity - M/M/∞ queues - Finite source model - M/G/1 queue (steady state solutions only) – Pollaczek – Khintchine formula – Special cases.Single and Multiple Server System. | |||||||||||||||||||||||||||||
Text Books And Reference Books: Text Books:
T1. Ross, S., “A first course in probability”, 9th Edition, Pearson Education, Delhi, 2012. T2. Medhi J., “Stochastic Processes”, 3rd Edition, New Age Publishers, New Delhi, Reprint 2014. (Chapters 2, 3, & 4) T3. T.Veerarajan, “Probability, Statistics and Random process”, 3rd Edition, Tata McGraw Hill, New Delhi, 2008.
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Essential Reading / Recommended Reading Reference Books: R1. Allen., A.O., “Probability, Statistics and Queuing Theory”, Academic press, New Delhi, 1981. R2. Taha, H. A., “Operations Research-An Introduction”, Seventh Edition, Pearson Education Edition Asia, Delhi, 2002. R3. Gross, D. and Harris, C.M., “Fundamentals of Queuing theory”, John Wiley and Sons, Second Edition, New York, 1985. | |||||||||||||||||||||||||||||
Evaluation Pattern Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks) End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks Mid Semester Examination (MSE) : Theory Papers:
End Semester Examination (ESE): The ESE is conducted for 100 marks of 3 hours duration. The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution. Question paper pattern is as follows. Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year The criteria for drawing the questions from the Question Bank are as follows 50 % - Medium Level questions 25 % - Simple level questions 25 % - Complex level questions | |||||||||||||||||||||||||||||
CS531P - COMPUTER NETWORKS (2021 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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To understand the concepts of data communications. To study the functions of different layers. To introduce IEEE standards employed in computer networking. To make the students to get familiarized with different protocols and network components. To build foundation of Networks in Algorithms and its analysis, Software Engineering Models |
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Course Outcome |
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CO1: Outline the basic concepts of reference models and the functionalities of physical layer in computer communications. CO2: Experiment with the data link layer protocols for error detection and corrections mechanism. CO3: Develop subnetting using IP addressing schemes and experiment with routing algorithms. CO4: Analyze the functionalities and features used in UDP and TCP protocols. CO5: Examine the Application layer protocols and cryptographic algorithms used in networking environment. |
Unit-1 |
Teaching Hours:9 |
DATA COMMUNICATIONS
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Introduction- Data communications: Components - Data Flow – Networks – Physical Structures – Network Types – Protocol Layering – TCP/IP Protocol Suite – OSI Model. Data and Signals –Digital Signals- Data Rate Limits- Performance- Digital Transmission – Digital to Digital Conversion- Line coding -Line coding Schemes –Transmission Media | |
Unit-2 |
Teaching Hours:9 |
DATA LINK LAYER
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Introduction – Link Layer Addressing – Error Detection and Correction-Cyclic Codes- Check sum- Forward Error correction –Data Link Layer Protocols- Automatic Repeat (ARQ) protocols -Stop and Wait, Go-back-N, Selective Repeat, HDLC, PPP Medium Access Control - Random Access Protocols -CSMA/CD, CSMA/CA, Channelization -FDMA-TDMA-CDMA, Wired LANs: IEEE Project 802.3, IEEE 802.4 - IEEE 802.5, Wireless LAN- IEEE Project 802.11, WiMAX -IEEE Project 802.16.
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Unit-3 |
Teaching Hours:9 |
NETWORK LAYER
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Introduction – Network-Layer Services– Packet Switching– Network-Layer Performance– IPv4 Addresses – Internet Protocol (IP)-IPV4 , ICMP V4, ARP, IPv6 , Subnetting Routing-Introduction - Routing Algorithms- Distance Vector Routing, Link State Routing, Path Vector Routing, Unicast Routing Protocols- RIP, OSPF, BGP -NAT
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Unit-4 |
Teaching Hours:9 |
TRANSPORT LAYER
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Transport Layer Protocols- UDP -Introduction – Services, Port Numbers, User Datagram Protocol- User Datagram, UDP Services, UDP Applications Transport Layer Protocols- TCP -Transmission Control Protocol- TCP Services, TCP features- TCP Connection- TCP Congestion control SCTP – SCTP Services, SCTP Features , Packet Format, Flow Control To Improve Qos.
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Unit-5 |
Teaching Hours:9 |
APPLICATION LAYER
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Application Layer -Introduction – DNS- SMTP- DHCP- FTP- HTTP-Telnet Cryptography and Network Security- Security Goals- Attacks- Confidentiality - Concepts of symmetric and asymmetric key cryptography-RSA, Sharing of symmetric keys - Diffie Hellman - Firewalls. Foundations of Modern Networking-Introduction: Software Defined Networking -SDN Architecture, Virtualization, The Internet of Things- Components
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Text Books And Reference Books: T1: Behrouz A. Forouzan, “Data communication and Networking with TCP/IP protocol suite”, Tata McGraw-Hill, Sixth Edition, 2021. ISBN 978-1-26-436335-3. | |
Essential Reading / Recommended Reading R1: James F. Kurose, Keith Ross, “Computer Networking: A Top-Down Approach Featuring the Internet”, Pearson Education, 2020. ISBN: 9780135928523. R2: Larry L. Peterson, Bruce S. Davie, Computer Networks: A Systems Approach Edition: 6th Edition, MK-Morgan Kaufmann/Elsevier-2021. ISBN: 978-0-12-818200-0. R3: Andrew S. Tanenbaum, Nick Feamster, David J. Wetherall, Computer Networks: 6th Edition, Pearson, 2021, ISBN 9780136764052. | |
Evaluation Pattern Continous internal assesment 70% End Semester Examination 30% | |
CS532 - INTRODUCTION TO ARTIFICIAL INTELLIGENCE (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course provides a strong foundation of fundamental concepts in Artificial Intelligence. To provide a basic exposition to the goals and methods and to enable the student to apply these techniques in applications which involve perception, reasoning and learning. |
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Course Outcome |
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CO1: Illustrate the basics of Artificial Intelligence and problem solving. CO2: Explain the various Searching Techniques. CO3: Outline the Adversial Search and CSP. CO4: Make use of Knowledge Engineering in real world representation. CO5: Apply the different Forms of Learning. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
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History - Applications – Components of AI - Intelligent Agents - Characteristics of Intelligent Agents - Agents and Environments - Good behavior – The nature of environments – structure of agents - Problem Solving - problem solving agents – Example problems– Searching for solutions. | |
Unit-2 |
Teaching Hours:9 |
SEARCHING TECHNIQUES
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Classical Search: Uniformed Search strategies - BFS - DFS- Bidirectional Search- Informed Heuristics Search Strategies -Heuristic function - Greedy - best -first search- A* Algorithm. local search algorithms and optimization problems –Hill-climbing Search, Simulated annealing, Local beam Search, Genetic algorithm -Searching with partial observations - Online Search Agents and Unknown Environment | |
Unit-3 |
Teaching Hours:9 |
GAME PLAYING and CSP
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Games – Optimal decisions in games –Min-Max algorithm- Alpha – Beta Pruning – imperfect real-time decision –Stochastic Games. Constraint Satisfaction Problem (CSP): Definition - Constraint propogation - Backtracking search - Local Search -The Structure of problems. | |
Unit-4 |
Teaching Hours:9 |
KNOWLEDGE REPRESENTATION
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Logic - Propositional logic - First order logic – Syntax and semantics for first order logic – Using first order logic – Knowledge engineering in first order logic. Inference in First order logic – propositional versus first order logic – unification and lifting – forward chaining – backward chaining - Resolution - Knowledge representation - Ontological Engineering - Categories and objects
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Unit-5 |
Teaching Hours:9 |
LEARNING
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Learning from Examples : Forms of Learning - Supervised learning - Learning Decision Trees - Regression and classification with linear models, Artificial Neural Network. Knowledge in Learning : Logical formulation of learning – Explanation based learning – Learning using relevant information – Inductive logic programming. Statistical learning- Learning with complete data - Learning with hidden variable | |
Text Books And Reference Books: T1. Stuart Russell and Peter Norvig, “Artificial Intelligence – A Modern Approach”, 4th Edition, Pearson Education, 2020. T2. Elaine Rich; Kevin Knight; Shivashankar B Nair, “Artificial Intelligence”, 3rd Edition, Tata McGraw-Hill, 2019. T3. Francois Chollet “Deep Learning with Python”, 1st Edition Manning Publication, 2018
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Essential Reading / Recommended Reading R1. Jeff Heaton, "Artificial Intelligence for Humans, Volume 1: Fundamental Algorithms",1st edition, CreateSpace Independent Publishing Platform, 2013 R2. George F. Luger, " Artificial Intelligence: Structures and Strategies for Complex Problem Solving", 6th Edition, Pearson Education,2021 R3.Kevin Warwick, " Artificial Intelligence: The Basics", Routledge, 2011 NPTEL Course: 1. Artificial Intelligence : Search Methods For Problem Solving By Prof. Deepak Khemani | IIT Madras 2. Fundamentals Of Artificial Intelligence By Prof. Shyamanta M. Hazarika | IIT Guwahati | |
Evaluation Pattern 1. Continuous Internal Assessment (CIA) for Theory 50% (50 marks out of 100 marks). 2. End Semester Examination (ESE): 50% (50 marks out of 100 marks). | |
CS533P - DESIGN AND ANALYSIS OF ALGORITHMS (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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To introduce basic concepts of algorithms; To introduce mathematical aspects and analysis of algorithms; To introduce sorting and searching algorithms; To introduce various algorithmic techniques; To introduce algorithm design methods. |
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Course Outcome |
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CO1: Demonstrate the process of algorithmic problem solving with time and space complexity. CO2: Identify algorithm design techniques for searching and sorting. CO3: Inspect algorithms under divide and conquer technique. CO4: Solve problems by applying dynamic programming technique and determine the efficiency of algorithms. CO5: Interpret the limitations of algorithm power and demonstrate backtracking technique. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION AND FUNDAMENTALS OF THE ANALYSIS OF ALGORITHM EFFICIENCY
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Introduction, Notion of Algorithm, Fundamentals of Algorithmic Solving, Important Problem Types, Fundamentals of the Analysis Framework, Mathematical Analysis of Non-recursive Algorithm, Mathematical Analysis of Recursive Algorithm and examples, Empirical Analysis of Algorithms and Algorithm Visualization. | |
Unit-2 |
Teaching Hours:9 |
ALGORITHM DESIGN TECHNIQUES
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Brute Force and Exhaustive Search: Selection Sort, Bubble Sort, Sequential Search and Brute-force string matching, Travelling Salesman Problem, Knapsack Problem, Assignment Problem. Decrease and Conquer: Insertion Sort and Topological Sorting and Fake Coin Problem, Russian Peasant Multiplication, Josephus Problem | |
Unit-3 |
Teaching Hours:9 |
ALGORITHM DESIGN TECHNIQUES
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Divide and conquer: Merge sort, Quick Sort, Binary Tree Traversals and Related Properties and Multiplication of Large Integers and Strassen’s Matrix Multiplication. Transform and Conquer: Presorting, Notion of Heap and Heapsort, Horner’s Rule and Binary Exponentiation. | |
Unit-4 |
Teaching Hours:9 |
ALGORITHM DESIGN TECHNIQUES
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Space and Time Trade - Offs: Sorting by Counting, Horspool’s and Boyer - Moore Algorithm for String Matching, Hashing. Dynamic Programming: Knapsack Problem, Warshall’s and Floyd’s Algorithm. Greedy Techniques: Prim’s Algorithm, Kruskal’s Algorithm, Dijkstra’s Algorithm. | |
Unit-5 |
Teaching Hours:9 |
ALGORITHM DESIGN TECHNIQUES
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Limitations of Algorithm Power: Decision Trees, P, NP and NP Complete Problems, Challenges in Numerical Algorithms. Backtracking: n-Queen’s Problem, Hamiltonian Circuit problem and Subset-Sum problem. Branch and Bound: Assignment problem, Knapsack problem and Traveling salesman problem. | |
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern
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CS541E01 - COMPUTER GRAPHICS WITH OPEN GL (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Computer Graphics with OpenGL is an introductory course that provides a comprehensive understanding of computer graphics' fundamental principles and techniques using the OpenGL (Open Graphics Library) programming interface. The course is designed to equip students with the knowledge and skills to create interactive 2D and 3D graphics applications. |
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Course Outcome |
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Unit-1 |
Teaching Hours:9 |
Introduction
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A survey of Computer Graphics, Video Display Devices, Raster-Scan Systems, Graphics Workstation and Viewing Systems, Input Devices, Hard-Copy Devices, Graphics Networks, Graphics on the Internet. | |
Unit-2 |
Teaching Hours:9 |
Output primitives & 2-D, 3-D Geometrical transforms
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Line Drawing Algorithms, DDA Algorithms, Bresenham's Line Algorithm, Circle-Generating Algorithms, Midpoint Circle Algorithms, Ellipse Algorithms, Basic Two-Dimensional Transformations, Matrix Representation, Three-Dimensional Translation, Three-Dimensional Rotation, Three-Dimensional Scaling, Other Three-Dimensional Transformations - Reflection and Shears. | |
Unit-3 |
Teaching Hours:9 |
Graphics in 2D with OpenGL
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Java Graphics in 2D, Two-Dimensional Graphics in Java, Transformations and Modeling, Basics of OpenGL and JOGL, Basic OpenGL 2D Programs, Into the Third Dimension, Drawing in 3D, Normal and Textures | |
Unit-4 |
Teaching Hours:9 |
3D viewing & Projections
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Projections ,Light & Material with Open GL Viewing and Projections, Perspective Projection, Orthographic Projection, Light and Material, Vision and Color, OpenGL Materials, OpenGL Lighting, Lights and Materials in Scenes, Textures, Texture targets, Mipmaps and Filtering, Texture Transformations, Creating Texture with OpenGL, Loading Data into Texture, Texture Coordinate Generation | |
Unit-5 |
Teaching Hours:9 |
Introduction to Unreal Engine
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Light and Material, Vision and Color, OpenGL Materials, OpenGL Lighting, Lights and Materials in Scenes, Case Study: Textures, Texture targets, Mipmaps and Filtering, Texture Transformations, Creating Texture with OpenGL, Loading Data into Texture, Texture Coordinate Generation, Texture Objects | |
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern Weightage for CIA: 50 Weightage for ESE: 50 | |
CS541E02 - INTERNET AND WEB PROGRAMMING (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Explain the tools for developing applications in Web programming; Describe the scripting languages –Java Script, Jquery and React js; Exposure to the backend platform using PHP and Node Js. |
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Course Outcome |
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CO1: . |
Unit-1 |
Teaching Hours:9 |
HTML5 and CSS3
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HTML5:
Introduction to HTML5 basic tags, Forms, Multimedia (video, audio) markup and APIs, Canvas, Data Storage, Drag & Drop, Messaging & Workers CSS3: Understanding basic CSS Syntax and Styles, Understanding Display, Position, and Document Flow, Changing and styling fonts, Adding transitions and animations, Introduction to usage of bootstrap and sass. | |
Unit-2 |
Teaching Hours:12 |
Java Script
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Java Script: Introduction, Java script function’s, methods and objects, Decisions and loops, Document Object, Model (DOM), JavaScript Events, Ajax and JSON, API, error handling and debugging, Filtering and Form enhancement, Introduction to Dynamic Web Programming, Implementing jQuery and JavaScript in Web Pages, Building Richly Interactive Web Pages with jQuery, Introducing jQuery UI, Getting started and building Web applications with angular JS. | |
Unit-3 |
Teaching Hours:6 |
React JS
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React js: Introduction, JSX in Depth, Data Flow and Life Cycle Events, Composite and Dynamic Components and Forms, Mixins and the DOM, React on the Server, React Addons, Performance of React Apps, React Router and Data Models, Animation, React Tools, Flux, Redux and React. | |
Unit-4 |
Teaching Hours:9 |
PHP
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Introduction to Server-Side Development with PHP, What is Server-Side Development, A Web Server’s Responsibilities, Quick Tour of PHP, Program Control, Functions, PHP Arrays and Super globals, Arrays, $_GET and $_POST Super global Arrays, $_SERVER Array, $_Files Array, Reading/Writing Files, PHP Classes and Objects, Object-Oriented Overview, Classes and Objects in PHP, Object Oriented Design, Error Handling and Validation, What are Errors and Exceptions?, PHP Error Reporting, PHP Error and Exception Handling, connectivity to database and processing the form. | |
Unit-5 |
Teaching Hours:9 |
CASE STUDY - Node.js
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The Node Module System, The Node Programming Model, Events and Timers, The Command Line Interface, The File System, Streams, Binary Data, Executing Code, Network Programming, HTTP. Node JS Database Connectivity, MVC Framework and Architecture, Web Hosting and Content Management System, Usage of Amazon storage for web application. | |
Text Books And Reference Books: TEXT BOOKS: 1. Bruce Lawson, Remy Sharp, “Introducing HTML 5”, Pearson Education, 2011. 2. Ian Lunn, “CSS3 Foundations”, Wiley Publishers, 2012. 3. Jon Duckett, “JavaScript and JQuery: Interactive Front-End Web Development”, Wiley Publishers: 2014. 4. Sams, “Teach Yourself AngularJS, JavaScript, and jQuery All in One”, Pearson Education ,2015. 5. Vipul A M, Prathomesh Sonpatki, “React JS by Example-Building Modern Web Application with React”, Packt Publishing,2019. 6. Colin J. Ihrig, “Pro Node.js for Developers”, APRESS, 2013. 7. Randy Connolly, Ricardo Hoar, "Fundamentals of Web Development”, 1 stEdition, Pearson Education India. (ISBN:978-9332575271)
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Essential Reading / Recommended Reading REFERENCE BOOKS: 1. Matt West, “HTML5 Foundations”, Wiley Publishers: 2012. 2. Training Guide Programming in HTML5 with JavaScript and CSS3 (MCSD) (Microsoft Press Training Guide), 2013. 3. Elizabeth Castro, Bruce Hyslop, “HTML and CSS: Visual QuickStart Guide” 8th edition, 2013. 4. Robin Nixon, “Learning PHP, MySQL &JavaScript with jQuery, CSS and HTML5”, 4 thEdition, O’Reilly Publications, 2015. (ISBN:978-9352130153) 2) Luke Welling, Laura Thomson, “PHP and MySQL Web Development”, 5th Edition, Pearson Education, 2016. (ISBN:978-9332582736) 5. Nicholas C Zakas, “Professional JavaScript for Web Developers”, 3rd Edition, Wrox/Wiley India, 2012. (ISBN:978-8126535088) 4) David Sawyer Mcfarland, “JavaScript & jQuery: The Missing Manual”, 1st Edition, O’Reilly/Shroff Publishers & Distributors Pvt Ltd, 2014 (ISBN:978- 9351108078) 6. Zak Ruvalcaba Anne Boehm, “Murach's HTML5 and CSS3”, 3rdEdition, Murachs/Shroff Publishers & Distributors Pvt Ltd, 2016. (ISBN:978-9352133246) | |
Evaluation Pattern
Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks) End Semester Examination (ESE): 50% (50 marks out of 100 marks)
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CS541E04 - CRYPTOGRAPHY AND NETWORK SECURITY (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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To understand the principles of encryption algorithms; conventional and public key cryptography. To have a detailed knowledge about authentication, hash functions and Network & application-level security mechanisms. |
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Course Outcome |
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CO1: Explain various features of Security mechanisms and services to study Standard Block Ciphers along with their design principles. CO2: Utilize the basic concepts and algorithms of public key encryption mechanism for secure data transmission. CO3: Compare various Cryptographic authentications protocols, Hash Functions, Algorithms and Standards. CO4: Identify Various Protocols and Standards in Network Security. CO5: Make use of various research directions at system level security. |
Unit-1 |
Teaching Hours:9 |
Introduction
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|
OSI Security Architecture, Classical Encryption techniques, Cipher Principles, DES, Crypto analysis of DES, AES, Block Cipher Design Principles and Modes of Operation, Triple DES, Placement of Encryption Function, Traffic Confidentiality. | |
Unit-2 |
Teaching Hours:9 |
Public Key Cryptography
|
|
Introduction to Number theory, Deffie Hellman Key Exchange, Key Management, Elliptic curve Cryptography, Confidentiality using Symmetric Encryption, Public Key Cryptography and RSA. | |
Unit-3 |
Teaching Hours:9 |
Authentication & Hash Functions
|
|
Authentication Requirements, Authentication Functions, Message Authentication Codes, Hash Functions, MD5, SHA, RIPEMD and HMAC Standards. | |
Unit-4 |
Teaching Hours:9 |
Network Security
|
|
Authentication Applications: Kerberos – X.509 Authentication Service – Electronic Mail Security – PGP – S/MIME - IP Security – Web Security. | |
Unit-5 |
Teaching Hours:9 |
Application Security
|
|
Intrusion detection – password management – Viruses and related Threats – Virus Counter measures – Firewall Design Principles – Trusted Systems, Secret sharing schemes, Probabilistic encryption, Quantum Encryption, Attribute and Identity Encryption CASE-Study. | |
Text Books And Reference Books: 1. William Stallings, “Cryptography and Network Security – Principles and Practices”, 6th Edition, 2016. 2. Bruce Schneier, “Applied Cryptography”, John Wiley & Sons Inc, 2015. | |
Essential Reading / Recommended Reading AtulKahate, “Cryptography and Network Security”, Tata McGraw-Hill, 2013. 2. Charles B. Pfleeger, Shari Lawrence Pfleeger, “Security in Computing”, Fifth Edition, Pearson Education, 2015. | |
Evaluation Pattern CIA 50 Marks ESE 50 Marks | |
CS581 - INTERNSHIP - I (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:1 |
Course Objectives/Course Description |
|
Internships are short-term work experiences that will allow a student to observe and participate in professional work environments and explore how his interests relate to possible careers. They are important learning opportunities through industry exposure and practices. Course Objectives: •Identify how the internship relates to their academic courses and preferred career path •Integrate existing and new technical knowledge for industrial application •Understand lifelong learning processes through critical reflection of internship experiences. •Articulate their experience and skills to potential employers |
|
Course Outcome |
|
CO1: . |
Unit-1 |
Teaching Hours:30 |
|||||||
Regulations
|
||||||||
1.The student shall undergo an Internship for30 days starting from the end of 4th semester examination and completing it during the initial period of 5th semester. 2.The department shall nominate a faculty as a mentor for a group of students to prepare and monitor the progress of the students. 3. The students shall report the progress of the internship to the mentor/guide at regular intervals and may seek his/her advise. 4. The Internship evaluation will be completed by the end of 5th semesters. 5. The students are permitted to carry out the internship outside India with the following conditions, the entire expenses are to be borne by the student and the University will not give any financial assistance. 6. Students can also undergo internships arranged by the department during vacation. 7. After completion of Internship, students shall submit a report to the department with the approval of both internal and external guides/mentors. 8. There will be an assessment for the internship for 1 credit, in the form of report assessment by the guide/mentor and a presentation on the internship given to department constituted panel. | ||||||||
Text Books And Reference Books: Nil | ||||||||
Essential Reading / Recommended Reading Nil | ||||||||
Evaluation Pattern Maximum Marks = 50(Only credit will be displayed in the score card) Passing marks 40% min Internship assessment will be carried out based on the following parameters, during the 5th semester as a single Presentation evaluation.
| ||||||||
CSHO533AIP - ROBOTICS AND PROCESS AUTOMATION (2021 Batch) | ||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
|||||||
Max Marks:100 |
Credits:4 |
|||||||
Course Objectives/Course Description |
||||||||
● To understand about RPA and its concepts ● Apply RPA tools and functionalities ● Understand the challenges and risks in RPA implementation
● Understand about bots and its usage in real time applications |
||||||||
Course Outcome |
||||||||
CO 1: Illustrate the advantages, techniques of RPA CO 2: Illustrate control flow and decision making CO 3: Experiment with automating desktop and web applications with exception handling CO 4: Experiment with automating different files. CO 5: Develop RPA projects. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
|
|
Introduction to RPA, what should be automated, what can be automated, Techniques of automation, Benefits of RPA, Components of RPA, RPA Platforms, Record and Play. | |
Unit-2 |
Teaching Hours:9 |
CONTROL FLOW AND DATA MANIPULATION
|
|
Variables: string variable, date time variable, number variable, Boolean variable; String Manipulation and List Variable; Data Table; Creating a first bot: working on a CSV file. | |
Unit-3 |
Teaching Hours:9 |
Unit III
|
|
Automating Web and Desktop applications; Interacting with active windows; Simulating keystroke and mouse activities; Triggers: Email trigger, Files and folder trigger, Hotkey trigger, Trigger loop; Exceptional Handling. | |
Unit-4 |
Teaching Hours:9 |
Unit 4
|
|
Working with Excel files; Working with PDF files; Automation using Email; Automation using word; Working with forms. Working with images. | |
Unit-5 |
Teaching Hours:9 |
Unit -V
|
|
RPA Challenge Website; Sales Order Processing; Using AI and RPA for Invoice Processing; Web Scrapping; Automated Customer Support Emails; Payroll Processing; Email Query Processing. | |
Text Books And Reference Books: T1. Mullakara, Nandan, and Arun Kumar Asokan. Robotic process automation projects: Build real-world RPA solutions using UiPath and Automation Anywhere. Packt Publishing Ltd, 2020.
T2. Husan Mahey. Robotics and Process Automation with Automation Anywhere, Packt Publishing Ltd, 2020. | |
Essential Reading / Recommended Reading NIL | |
Evaluation Pattern CIA:70 ESE:30 | |
CSHO533CSP - CYBER FORENSICS AND MALWARE DETECTION (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
|
To analyze about best possible solutions for different vulnerabilities that are exploited for hacking |
|
Course Outcome |
|
CO1: To understand the fundamentals of Cyber forensic over different platforms. CO2: To understand concepts of Malware Forensics; Web Attack Forensics; Bitcoin Forensics; Cyber Laws and Data Recovery & Analysis CO3: To understand the nature of malware, its capabilities, and how it is combated through
detection and classification CO4: To apply the tools and methodologies used to perform static and dynamic analysis on
unknown executables. CO5: To understand the malware functionality and malware detection techniques |
Unit-1 |
Teaching Hours:9 |
Unit-1
|
|
Introduction to Cyber Forensics; Windows Forensics; Linux Forensics, Mac OS Forensics; Anti-forensics; Network Forensics; Mobile Forensics; Cloud Forensics | |
Unit-2 |
Teaching Hours:9 |
UNIT-II
|
|
Malware Forensics; Web Attack Forensics; Emails and Email Crime, Bitcoin Forensics; Cyber Law and Cyberwarfare; Data Recovery & Data Analysis | |
Unit-3 |
Teaching Hours:9 |
UNIT-III
|
|
Introduction to malware, OS security concepts, malware threats, evolution of malware, malware types- viruses, worms, rootkits, Trojans, bots, spyware, adware, logic bombs, malware analysis, static malware analysis, dynamic malware analysis | |
Unit-4 |
Teaching Hours:9 |
UNIT-IV
|
|
STATIC ANALYSIS: Analyzing Windows programs, Anti-static analysis techniques- obfuscation, packing, metamorphism, polymorphism DYNAMIC ANALYSIS: Live malware analysis, dead malware analysis, analyzing traces of malware- system-calls, api-calls, registries, network activities. Anti-dynamic analysis techniques-anti-vm, runtime-evasion techniques, Malware Sandbox, Monitoring with Process Monitor, Packet Sniffing with Wireshark, Kernel vs. User-Mode Debugging, OllyDbg, Breakpoints, Tracing, Exception Handling, Patching | |
Unit-5 |
Teaching Hours:9 |
UNIT-V
|
|
Malware Functionality: Downloader, Backdoors, Credential Stealers, Persistence Mechanisms, Privilege Escalation, Covert malware launching- Launchers, Process Injection, Process Replacement, Hook Injection, Detours, APC injection Malware Detection Techniques: Signature-based techniques: malware signatures, packed malware signature, metamorphic and polymorphic malware signature Non-signature based techniques: similarity-based techniques, machine-learning methods, invariant inferences | |
Text Books And Reference Books: Text Books: T1. Practical Cyber Forensics: An Incident-Based Approach to Forensic Investigations: Reddy, Niranjan, Published by Apress, Berkeley, CA, DOIhttps://doi.org/10.1007/978-1-4842-4460- 9, Print ISBN 978-1-4842-4459-3, 2019 T2. Practical malware analysis The Hands-On Guide to Dissecting Malicious Software by Michael Sikorski and Andrew Honig ISBN-10: 159327-290-1, ISBN-13: 978-1-59327-290-6, 2012
| |
Essential Reading / Recommended Reading Reference Books: R1. Malware Detection A Complete Guide - 2019 Edition, Gerardus Blokdyk, Published by 5STARCooks, 2019, ISBN: 0655900845, 9780655900849 | |
Evaluation Pattern CIA 70% ESE 30% | |
CSHO533DAP - BIG DATA SECURITY ANALYTICS (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
|
To provide the fundamental techniques and principles of security model in Big Data. |
|
Course Outcome |
|
Unit-1 |
Teaching Hours:9 |
SECURITY MODELS
|
|
Critical characteristics of Information - NSTISSC Security Model -Components of information System –SDLC – Information assurance - Security Threats and vulnerabilities - Overview of Security threats-– Security Standards. | |
Unit-2 |
Teaching Hours:9 |
WEB SECURITY
|
|
Introduction, Basic security for HTTP Applications and Services, Basic Security for SOAP Services, Identity Management and Web Services, Authorization Patterns, Security Considerations, Challenges. | |
Unit-3 |
Teaching Hours:9 |
NETWORK SECURITY
|
|
Network security - Intrusion Prevention, detection, and Management - Firewall – Ecommerce Security - Computer Forensics - Security for VPN and Next Generation Networks. | |
Unit-4 |
Teaching Hours:9 |
ATTACKS & SECURITY MECHANISMS
|
|
Host and Application security -Control hijacking, Software architecture and a simple buffer overflow - Common exploitable application bugs, shellcode - Buffer Overflow - Side-channel attacks - Timing attacks, power analysis, cold-boot attacks, defenses – Malware - Viruses and worms, spyware, key loggers, and botnets; defenses auditing, policy - Defending weak applications - Isolation, sandboxing, virtual machines. | |
Unit-5 |
Teaching Hours:9 |
DIGITAL WATER MARKING
|
|
Introduction, Difference between Watermarking and Steganography, Types and techniques (Spatial-domain, Frequency-domain, and Vector quantization-based watermarking), Attacks and Tools (Attacks by Filtering, Remodulation, Distortion, Geometric Compression, Linear Compression), Watermark security & authentication. | |
Text Books And Reference Books: 1. William Stallings, “Cryptography and Network Security: Principles and Practice”, 6th Edition,PHI, 2014. 2. Michael E. Whitman and Herbert J Mattord, "Principles of Information Security", 6th edition,Vikas Publishing House, 2017. 3. Peter Wayner, Disappearing Cryptography–Information Hiding: Steganography & Watermarking, Morgan Kaufmann Publishers, New York, 2002. 4. Ingemar J. Cox, Matthew L. Miller, Jeffrey A. Bloom, Jessica Fridrich, TonKalker, Digital Watermarking and Steganography, Margan Kaufmann Publishers, New York, 2008. | |
Essential Reading / Recommended Reading 1. Bill Nelson, Amelia Phillips, F.Enfinger and Christopher Stuart, “Guide to Computer Forensics and Investigations, 4 th ed., Thomson Course Technology, 2010. 2. Matt Bishop, “Computer Security: Art and Science”, 1 st edition, Addison-Wesley Professional, 2015. 3. Neil F. Johnson, Zoran Duric, Sushil Jajodia, Information Hiding: Steganography and Watermarking-Attacks and Countermeasures, Springer, 2012. 4. Stefan Katzenbeisser, Fabien A. P. Petitcolas, Information Hiding Techniques for Steganography and Digital Watermarking, Artech House Print on Demand, 1999. | |
Evaluation Pattern CIA - 70 Marks ESE - 30 Marks | |
CSHO534AIP - COMPUTER VISION (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
|
· To provide an introduction to concepts in Computer Vision including fundamental Image Processing Operations, Image enhancement, edge detection, Texture, boundary, shape and motion analysis, object segmentation, image transformation and 3D vision. To provide practical experience in implementing Computer Vision algorithms. |
|
Course Outcome |
|
CO1: Experiment with basic image processing operations ? filtering, Morphology and thresholding. CO2: Develop programs for the detection of edges, corners, points of interest and for texture analysis CO3: Experiment with shape analysis algorithms. CO4: Apply object segmentation and shape modelling for object detection and extraction. CO5: Construct Computer Vision solution for a given problem |
Unit-1 |
Teaching Hours:9 |
Unit-1
|
|
Images and imaging operations – Image filtering and morphology – Thresholding. | |
Unit-2 |
Teaching Hours:9 |
Unit-2
|
|
Edge detection, Corner, interest point, and invariant feature detection – Texture analysis | |
Unit-3 |
Teaching Hours:9 |
Unit-3
|
|
Binary shape analysis – Boundary pattern analysis –Line, Circle, and Ellipse detection – generalized Hough transform | |
Unit-4 |
Teaching Hours:9 |
Unit-4
|
|
Object Segmentation and shape models - The three Dimensional world – Perspective n-point problem – invariants and perspective | |
Unit-5 |
Teaching Hours:9 |
Unit-5
|
|
Image transformation and camera calibration – Motion. Case studies – Face detection and recognition, surveillance , In-vehicle vision systems | |
Text Books And Reference Books: T1. E.R. Davies, Computer Vision: Principles, Algorithms, Applications, Learning, 5e, AP, 2018 | |
Essential Reading / Recommended Reading R1. Ponce Jean & Forsyth David , Computer Vision: A Modern Approach, 2e, Pearson, 2015 R2. Richard Szeliski, Computer vision: Algorithms and Applications, 1e, Springer, 2010 R3. J. R. Parker, Algorithms for Image Processing and Computer Vision, 2e, Wiley, 2010 | |
Evaluation Pattern CIA -70 Marks ESE - 30 Marks | |
CSHO534CSP - INTRUSION DETECTION AND INCIDENT RESPONSE (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
|
After learning the course for a semester, the student will be aware of the intrusion detections concepts in cyber-attacks and its corresponding preventions and incident responses to ensure the data is recovered in time and whole system is operational. The student would also get a clear idea on some of the cases with their analytical studies in IDS and Incident responses. |
|
Course Outcome |
|
CO 1: Explain the evolution from design protection to detection of intrusions CO 2: Summarize the various intrusion detection system and its architectural models CO 3: Identify the incident response when a computer intrusion occurs. CO 4: Analyze the parameters needed to detect intrusions CO 5: Evaluate the best practices that comprise intrusions with incident responses. |
Unit-1 |
Teaching Hours:9 |
UNIT 1
|
|
Introduction to computer incident, legal environment, Network security and attacks, basics of incident detection, parameters for assessment of intrusion detection, Intrusion detection system and Detection approaches, Misuse detection, anomaly detection, specification based detection, Hybrid detection and statistics | |
Unit-2 |
Teaching Hours:9 |
UNIT 2
|
|
Centralized, Distributed, Cooperative Intrusion Detection, Tiered architecture, Intrusion detection in security, Tool Selection and Acquisition Process, Bro Intrusion Detection, Prelude Intrusion Detection, Cisco Security IDS, Snorts Intrusion Detection, NFR security, Architecture models of IDs and IPs | |
Unit-3 |
Teaching Hours:9 |
UNIT 3
|
|
Basics of Incident Response, Preparing for Incident Response, Live Data Collection, Preparation, Identification, Containment, Eradication, Recovery | |
Unit-4 |
Teaching Hours:9 |
UNIT 4
|
|
Introduction to legal evidence preparation for incident response, Forensics Duplication, Network Surveillance/Evidence, statistical Analysis Investigating Windows, Investigating Unix, Malware Triage, ways of detecting residual after attacks | |
Unit-5 |
Teaching Hours:9 |
UNIT 5
|
|
Case studies: various intrusion scenarios and their incident response and evidence gathering along with possible solutions. | |
Text Books And Reference Books:
| |
Essential Reading / Recommended Reading
| |
Evaluation Pattern CIA 50 Marks ESE 50 marks | |
CSHO534DAP - WEB ANALYTICS (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
|
This Web Analytics course covers fundamental concepts of web analytics and dives deep into web, social and content and analytics, illustrating common analytical scenarios and how to use popular web analytics tools used by marketers across the major industry domains. The course approaches web analytics from a strategic and practical perspective, showcasing techniques for using Google Web analytics and other platforms and tools. You’ll keep pace with the most important analytics trends and prepare for a career in web and digital analytics. |
|
Course Outcome |
|
CO1: Demonstrate the fundamental concepts of web analytics. CO2: Illustrate various competitive intelligence analysis in web analytics. CO3: Analyze and Examine Social, Mobile and Video Emerging Analytics. CO4: Examine working of Google Analytics and creating an Implementation Plan. CO5: Develop Google Analytics Accounts and Profiles. |
Unit-1 |
Teaching Hours:9 |
Web Analytics 2.0
|
|
The Bold New World of Web Analytics 2.0 State of the Analytics Union, State of the Industry, Rethinking Web Analytics: Meet Web Analytics 2.0 The Awesome World of Clickstream Analysis: Metrics Eight Critical Web Metrics:Visits and Visitors, Time on Page and Time on site, Bounce Rate, Exit Rate, Conversion rate, Engagement. Web Metrics Demystified, Strategically-aligned Tactics for Impactful Web Metrics | |
Unit-2 |
Teaching Hours:9 |
Competitive Intelligence Analysis
|
|
Competitive Intelligence Analysis CI Data Sources: Toolbar Data, Panel Data, ISP(Network) Data, Search Types and Secrets Website Traffic Analysis: Comparing Long Term Traffic Trends, Analyzing Competitive Sites Overlap and Opportunities, Analyzing Referrals and Destinations Search and Keyword Analysis Top Keywords Performance Trend, Geographic Interest and Opportunity Analysis, Related and Fast Rising searches, Share-of Shelf Analysis, Competitive Keyword Advantage Analysis, Keyword Expansion Analysis | |
Unit-3 |
Teaching Hours:9 |
Emerging Analytics: Social, Mobile and Video
|
|
Emerging Analytics: Social, Mobile and Video Measuring the New Social Web: The Data Challenge, The Content Democracy Evaluation, The Twitter Revolution Analyzing Offline Customer Experiences(applications), Analyzing mobile customer Experience: Mobile Data Collection, Mobile Reporting and Analysis Measuring the success of Blogs: Raw Author Contribution, Holistic Audience growth, Citations and Ripple Index, Cost of Blogging, Benefit(ROI) from Blogging Quantifying the Impact of Twitter: Growth in Number of Followers, Message Amplification, Click-Through Rates and Conversions, Conversation Rate, Emerging Twitter Metrics Analyzing Performance of Videos Data Collection for Videos, Key Video Metrics and Analysis, Advanced Video Analysis | |
Unit-4 |
Teaching Hours:9 |
Case Study: Google Analytics- Part 1
|
|
Case Study: Google Analytics- Part 1 Defining Web Analytics, What Google Analytics Contributes, How Google Analytics Fits in the Analytics Ecosystem. Creating An Implementation Plan: Gather Business Requirements, Analyze and Document Website Architecture, Create an account and configure your profile, Configure the tracking code ad tag pages, Tag Marketing Campaigns, Create Additional User Accounts and Configure Reporting ,Perform operational Configuration Steps Under the Covers: How Google Analytics works Data Collection and Processing, Reports, About the tracking code, Understanding Page views. | |
Unit-5 |
Teaching Hours:9 |
Case Study: Google Analytics- Part 2
|
|
Case Study: Google Analytics- Part 2 Tracking Visitor Clicks, Outbound Links and Non HTML Files About the Tracking Cookies Google Analytics Accounts and Profiles Google Analytics Accounts, Creating a Google Analytics Account: Creating Additional Profiles, Access Levels, All about Profiles: Basic Profile Settings, Profile Name, Website URL, Time Zone, Default Page, Exclude URL Query Parameters, E-commerce settings, Tracking On-site Search, Applying Cost Data. Analyze Website Visitors with Google Analytics Segments: Define segments | |
Text Books And Reference Books: Text Books:
| |
Essential Reading / Recommended Reading Reference Books:
Online Resources: | |
Evaluation Pattern Continuous Internal Assessment (CIA): 70% (70 marks out of 100 marks) End Semester Examination (ESE): 30% (30 marks out of 100 marks) | |
ECOE5601 - EMBEDDED BOARDS FOR IOT APPLICATIONS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
The aim of this course is to introduce the architecture, programming and interfacing of peripheral devices with embedded boards for IOT applications and design IOT based smart applications. |
|
Course Outcome |
|
CO-1: Understand the architecture, programming and interfacing principles of ATMEGA32 AVR microcontroller and Rasberry P |
Unit-1 |
Teaching Hours:9 |
NETWORKING SENSORS
|
|
Network Architecture - Sensor Network Scenarios- Optimization Goals and Figures of Merit- Physical Layer and Transceiver Design Considerations-MAC Protocols for Wireless Sensor Networks- Introduction of sensors and transducers. | |
Unit-2 |
Teaching Hours:9 |
ARDUINO BOARD AND its? INTERFACING
|
|
ATMEGA328 microcontroller - Architecture- memory organisation – Operating modes – On chip peripherals- Embedded communication interfaces- Example programs using Arduino IDE- Integration of peripherals (Buttons & switches, digital inputs, Matrix keypad, Basic RGB color-mixing, electromechanical devices- Displays- sensors(Temperature, Pressure, Humidity, Water level etc.), camera, real time clock, relays, actuators, Bluetooth, Wi-fi). | |
Unit-3 |
Teaching Hours:9 |
IoT BASED SYSTEM DESIGN
|
|
Definition of IoT- Applications and Verticals- System Architecture-Typical Process Flows-Technological Enablers- Open Standard Reference Model- Design Constraints and Considerations- IoT Security- Experiments using Arduino Platform | |
Unit-4 |
Teaching Hours:9 |
RASBERRY-PI
|
|
Introduction to Raspberry pi – configuration of Raspberry pi – programming raspberry pi - Implementation of IOT with Rasberry pi | |
Unit-5 |
Teaching Hours:9 |
IMPLEMENTATION
|
|
{This unit is entirely practical based} Implementation of a IOT based real time system. The concept of the specific embedded design has to be discussed. Eg: Smart Irrigation using IOT/ IoT Based Biometrics Implementation on Raspberry Pi/ Automation etc. Note: Unit – V will be based on a group project. Each group comprising of maximum 3 members. Any microcontroller can be used in Unit-V. | |
Text Books And Reference Books: T1. Slama, Dirak “Enterprise IOT : Strategies and Best Practices for Connected Products and services”, Shroff Publisher, 1st edition, 2015 T2. Ali Mazidi, Sarmad Naimi, Sepehr Naimi “AVR Microcontroller and Embedded Systems: Using Assembly and C”, Pearson 2013 T3. Wentk, “Richard Raspberry Pi”, John Wiley & Sons, 2014 | |
Essential Reading / Recommended Reading R1. .K. Ray & K.M.Bhurchandi, “Advanced Microprocessors and peripherals- Architectures, Programming and Interfacing”, Tata McGraw Hill, 2002 reprint R2. Gibson, “Microprocessor and Interfacing” Tata McGraw Hill,II edition, 2009 R3. Muhammad Ali Mazidi, Rolin D. Mckinlay, Danny Causey “8051 Microcontroller and Embedded Systems using Assembly and C” Prentice Hall of India, 2008 | |
Evaluation Pattern CIA 1, CIA 2, CIA 3, ESE (As per the university norms) | |
ECOE5602 - FUNDAMENTALS OF IMAGE PROCESSING (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
The aim of this course is to introduce image processing fundamentals making the students to understand the different methods available to process an image and also give them an insight about the toolbox in MATLAB which can be used to do simulations in image processing. |
|
Course Outcome |
|
CO1: Understand the basic principles of image processing CO2: Understand the tools used for image processing applications CO3: Analyze the methods used for image preprocessing CO4: Apply the compression techniques and analyze the results CO5: Develop an image processing system for a given application
|
Unit-1 |
Teaching Hours:9 |
|||
DIGITAL IMAGE FUNDAMENTALS
|
||||
Concept of Digital Image, conversion of analog image to digital, General Applications of image processing, Fundamental Steps in Digital Image Processing. Components of an Image Processing System. Elements of Visual Perception. Light and the Electromagnetic Spectrum. Image Sensing and Acquisition. Image Sampling and Quantization | ||||
Unit-2 |
Teaching Hours:9 |
|||
MATLAB USING IP TOOL BOX
|
||||
Introduction to MATLAB, Introduction to IP Tool box, Exercises on image enhancement, image restoration, and image segmentation, Fourier Transform, Discrete Fourier Transform and Discrete Cosine Transform | ||||
Unit-3 |
Teaching Hours:9 |
|||
IMAGE PROCESSING TECHNIQUES PART 1
|
||||
Image Enhancement in the Spatial Domain: Some Basic Gray Level Transformations. Histogram Processing. Enhancement Using Arithmetic/Logic Operations. Basics of Spatial Filtering. Smoothing Spatial Filters. Sharpening Spatial Filters. Importance of Image Restoration, Model of the Image Degradation/Restoration Process. Noise Models. Filters for Image Restoration: Minimum Mean Square Error (Wiener) Filtering. Constrained Least Squares Filtering. Geometric Mean Filter | ||||
Unit-4 |
Teaching Hours:9 |
|||
IMAGE PROCESSING TECHNIQUES PART 2
|
||||
Image Compression: Fundamentals. Image Compression Models. Elements of Information Theory. Error-Free Compression. Lossy Compression. Image Compression Standards. Image Segmentation: Detection of Discontinuities. Edge Linking and Boundary Detection. Thresholding. Region-Based Segmentation. Segmentation by Morphological Watersheds | ||||
Unit-5 |
Teaching Hours:9 |
|||
APPLICATION OF IMAGE PROCESSING
|
||||
Applications of image processing in the field of Biomedical, Remote sensing, Machine vision, Pattern recognition, and Microscopic Imaging | ||||
Text Books And Reference Books: T1.Gonzalez and woods, Digital Image Processing using MATLAB, PHI, 2005 | ||||
Essential Reading / Recommended Reading No reference books
| ||||
Evaluation Pattern Evaluation Pattern
| ||||
ECOE5603 - OBSERVING EARTH FROM SPACE (2021 Batch) | ||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
|||
Max Marks:100 |
Credits:3 |
|||
Course Objectives/Course Description |
||||
The aim of this course is to understand the basics and applications of Satellite Remote Sensing, become familiar with the usage of active and Passive remote Sensing from space and explore the applications of Satellite Remote Sensing from Ecology to National Security. The course will include some simple python based Jupyter Notebooks and open-source Remote Sensing resources. The course will introduce students to a career in Satellite remote sensing |
||||
Course Outcome |
||||
CO1: Understand the basics and applications of Satellite Remote Sensing CO2: Describe usage of Passive remote Sensing from space CO3: Explain the applications of active remote sensing from space CO4: Understand the applications of Satellite Remote Sensing in Agriculture, Forest Biomass Measurement, Security and Geodesy CO5: Apply the fundamentals of satellite and remote sensing for hazardoues and disaster management uses. |
Unit-1 |
Teaching Hours:9 |
|||
BASICS Of SATELLITES AND SATELLITE IMAGERY
|
||||
History of Satellites, Types and Classification of Satellites, Launching of Satellites, orbits, attitude and orbit control, Satellite imagery and basics of Satellite datasets, Satellite Imagery for UN SDG, Satellite data analysis | ||||
Unit-2 |
Teaching Hours:9 |
|||
INTRODUCTION TO PASSIVE SATELLITE IMAGERY
|
||||
Concept of Imaging Spectroscopy, Difference between multispectral and hyperspectral, Spectral features, Types of Spectrometer Sensors and missions,resolution,AI and ML in satellite image analysis, Introduction to python and Jupyter notebooks for satellite image analysis | ||||
Unit-3 |
Teaching Hours:9 |
|||
INTRODUCTION TO ACTIVE SATELLITE IMAGERY
|
||||
Active imaging technology, radar range equation and its Implications, using amplitude phase and polarity of returned signals to measure target parameters,scattering matrix and its decomposition, Introduction to EarthEngine and Sentinel Hub | ||||
Unit-4 |
Teaching Hours:9 |
|||
LAND APPLICATIONS
|
||||
Use of Satellite Remote Sensing in Agriculture, Forest Biomass Measurement, Security and Geodesy | ||||
Unit-5 |
Teaching Hours:9 |
|||
HAZARD AND DISASTER MANAGEMENT
|
||||
Hazards and Disaster Management as per UN SDG, Use of Satellite Remote Sensing in predicting/monitoring floods, Earthquakes, volcanoes and Fires | ||||
Text Books And Reference Books: T1. Rebekah B. Ismaili, “Earth Observation Using Python”, Wiley, 2021, Satellite Communication Anil Mainy Wiley 2010 T2. Ruiliang Pu, Hyperspectral Remote Sensing Fundamentals and Practice ,CRC Press 2017 T3. The SAR Handbook. NASA & Servir Global T4. Liguo Wong,Chunhui Zhao,Hyperspectral Image Processing,Springer 2015 T5. Matteo Pastorino and Andrea Randazzo, “ Microwave Imaging Methods and Applications”, Artech House, 2018 | ||||
Essential Reading / Recommended Reading R1. Dimitri G. Manolakis Hyperspectral Imaging Remote Sensing Physics, Sensors, and Algorithms,Cambridge University Press,2016 R2. Smith, B., Carpentier, M.H, “ The Microwave Engineering Handbook-Microwave systems and applications”, Springer | ||||
Evaluation Pattern Evaluation Pattern
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EEOE531 - HYBRID ELECTRIC VEHICLES (2021 Batch) | ||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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This course introduces the fundamental concepts, principles, analysis and design of hybrid and electric vehicles. |
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Course Outcome |
||||
· To understand concepts of hybrid and electric drive configuration, types of electric machines that can be used, suitable energy storage devices etc · To recognize the application of various drive components and selection of proper component for particular applications. |
Unit-1 |
Teaching Hours:12 |
HYBRID VEHICLES
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History and importance of hybrid and electric vehicles, impact of modern drive-trains on energy supplies. Basics of vehicle performance, vehicle power sources, transmission characteristics, and mathematical models to describe vehicle performance. | |
Unit-2 |
Teaching Hours:12 |
HYBRID TRACTION
|
|
Basic concept of hybrid traction, introduction to various hybrid drive-train topologies, power flow control in hybrid drive-train topologies, fuel efficiency analysis. Basic concepts of electric traction, introduction to various electric drive-train topologies, power flow control in hybrid drive-train topologies, fuel efficiency analysis. | |
Unit-3 |
Teaching Hours:12 |
MOTORS AND DRIVES
|
|
Introduction to electric components used in hybrid and electric vehicles, configuration and control of DC Motor drives, Configuration and control of Induction Motor drives, configuration and control of Permanent Magnet Motor drives, Configuration and control of Switch Reluctance Motor drives, drive system efficiency. | |
Unit-4 |
Teaching Hours:12 |
INTEGRATION OF SUBSYSTEMS
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|
Matching the electric machine and the internal combustion engine (ICE), Sizing the propulsion motor, sizing the power electronics, selecting the energy storage technology, Communications, supporting subsystems | |
Unit-5 |
Teaching Hours:12 |
ENERGY MANAGEMENT STRATEGIES
|
|
Introduction to energy management strategies used in hybrid and electric vehicle, classification of different energy management strategies, comparison of different energy management strategies, implementation issues of energy strategies. | |
Text Books And Reference Books: 1. BimalK. Bose, ‘Power Electronics and Motor drives’ , Elsevier, 2011 2. IqbalHussain, ‘Electric and Hybrid Vehicles: Design Fundamentals’, 2nd edition, CRC Pr I Llc, 2010 | |
Essential Reading / Recommended Reading 1. Sira -Ramirez, R. Silva Ortigoza, ‘Control Design Techniques in Power Electronics Devices’, Springer, 2006 2. Siew-Chong Tan, Yuk-Ming Lai, Chi Kong Tse, ‘Sliding mode control of switching Power Converters’, CRC Press, 2011 3. Ion Boldea and S.A Nasar, ‘Electric drives’, CRC Press, 2005 | |
Evaluation Pattern CIA I - 20 marks CIA II -midsem 50 marks CIA III - 20 marks ESE - 100 marks | |
EEOE532 - ROBOTICS AND AUTOMATION (2021 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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· To understand concepts in kinematics and dynamics of robotic system. · To introduce control strategies of simple robotic system. · To study the applications of computer based control to integrated automation systems. |
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Course Outcome |
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CO 1: To understand the basic concepts in robotics. CO 2: To describe basic elements in a robotic system CO 3: To understand the kinematics, dynamics and programming with respect to a robotic system. CO 4: To understand the control system design for a robotic system CO 5: To discuss some of the robotic applications |
Unit-1 |
Teaching Hours:12 |
Introduction
|
|
Robot definitions - Laws of robotics - Robot anatomy - History - Human systems and Robotics - Specifications of Robots - Flexible automation versus Robotic technology - Classification applications | |
Unit-2 |
Teaching Hours:12 |
Robotic systems
|
|
Basic structure of a robot – Robot end effectors - Manipulators - Classification of robots – Accuracy - Resolution and repeatability of a robot - Drives and control systems – Mechanical components of robots – Sensors and vision systems - Transducers and sensors - Tactile sensors – Proximity sensors and range sensors - Vision systems - RTOS - PLCs - Power electronics | |
Unit-3 |
Teaching Hours:12 |
Robot kinematics, dynamics and programming
|
|
Matrix representation - Forward and reverse kinematics of three degree of freedom – Robot Arm – Homogeneous transformations – Inverse kinematics of Robot – Robo Arm dynamics - D-H representation of forward kinematic equations of robots - Trajectory planning and avoidance of obstacles - Path planning - Skew motion - Joint integrated motion – Straight line motion - Robot languages- Computer control and Robot programming/software | |
Unit-4 |
Teaching Hours:12 |
Control system design
|
|
Open loop and feedback control - General approach to control system design - Symbols and drawings - Schematic layout - Travel step diagram, circuit and control modes - Program control - Sequence control - Cascade method - Karnaugh-Veitch mapping - Microcontrollers - Neural network - Artificial Intelligence - Adaptive Control – Hybrid control | |
Unit-5 |
Teaching Hours:12 |
Robot applications
|
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Material handling - Machine loading, Assembly, inspection, processing operations and service robots - Mobile Robots - Robot cell layouts - Robot programming languages | |
Text Books And Reference Books: 1. Nagrath and Mittal, “Robotics and Control”, Tata McGraw-Hill, 2003. 2. Spong and Vidhyasagar, “Robot Dynamics and Control”, John Wiley and sons, 2008. 3. S. R. Deb and S. Deb, ‘Robotics Technology and Flexible Automation’, Tata McGraw Hill Education Pvt. Ltd, 2010. | |
Essential Reading / Recommended Reading 1. Saeed B. Niku, ‘Introduction to Robotics’,Prentice Hall of India, 2003. 2. Mikell P. Grooveret. al., "Industrial Robots - Technology, Programming and Applications", McGraw Hill, New York, 2008. | |
Evaluation Pattern CIA I -20 marks CIA II - midsem 50 marks CIA III - 20 marks ESE - 100 marks | |
EEOE533 - SMART GRIDS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Introducing the concepts of various components of Smart Grid, and their impacts on the energy industry, including renewable integration, PHEV penetration, demand side management, and greenhouse gas (GHG) emissions reductions. Energy policy modelling and analysis, such as policies on GHG emissions reductions and incentives to green energy investments, will be integrated into the course as well. |
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Course Outcome |
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CO1: Understand the difference between Smart Grid (SG) vs. Conventional power system (CPS). CO2: Explore different types of technologies associated with SG and its operational management at consumer level. CO3: Analyze different types of technologies associated with SG and its operational management at substation level. CO4: Understand different information and communication technologies suitable for SG environment. CO5: Understand different ways for handing power quality issues in SG environment at different stages. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION TO SMART GRID
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Evolution of Electric Grid, Concept of Smart Grid, Definitions, Need of Smart Grid, Functions of Smart Grid, Opportunities & Barriers of Smart Grid, Difference between conventional & smart grid, Concept of Resilient &Self Healing Grid, Present development & International policies in Smart Grid. Case study of Smart Grid.CDM opportunities in Smart Grid. | |
Unit-2 |
Teaching Hours:9 |
SMART GRID TECHNOLOGIES: PART 1
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Introduction to Smart Meters, Real Time Prizing, Smart Appliances, Automatic Meter Reading(AMR), Outage Management System(OMS), Plug in Hybrid Electric Vehicles(PHEV), Vehicle to Grid, Smart Sensors, Home & Building Automation, Phase Shifting Transformers. | |
Unit-3 |
Teaching Hours:9 |
SMART GRID TECHNOLOGIES: PART 2
|
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Smart Substations, Substation Automation, Feeder Automation. Geographic Information System(GIS), Intelligent Electronic Devices(IED) & their application for monitoring &protection, Smart storage like Battery, SMES, Pumped Hydro, Compressed Air Energy Storage, Wide Area Measurement System(WAMS), Phase Measurement Unit (PMU). | |
Unit-4 |
Teaching Hours:9 |
INFORMATION AND COMMUNICATION TECHNOLOGY FOR SMART GRID
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|
Advanced Metering Infrastructure (AMI), Home Area Network (HAN), Neighborhood Area Network (NAN), Wide Area Network (WAN). Bluetooth, ZigBee, GPS, Wi-Fi, Wi-Max based communication, Wireless Mesh Network, Basics of CLOUD Computing & Cyber Security for Smart Grid. Broadband over Power line (BPL). IP based protocols. | |
Unit-5 |
Teaching Hours:9 |
POWER QUALITY MANAGEMENT IN SMART GRID
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Power Quality & EMC in Smart Grid, Power Quality issues of Grid connected Renewable Energy Sources, Power Quality Conditioners for Smart Grid, Web based Power Quality monitoring, Power Quality Audit. | |
Text Books And Reference Books: 1. Ali Keyhani, Mohammad N. Marwali, Min Dai “Integration of Green and Renewable Energy in Electric Power Systems”, Wiley 2. Clark W. Gellings, “The Smart Grid: Enabling Energy Efficiency and Demand Response”,CRC Press 3. JanakaEkanayake, Nick Jenkins, KithsiriLiyanage, Jianzhong Wu, Akihiko Yokoyama,“Smart Grid: Technology and Applications”, Wiley 4. Jean Claude Sabonnadière, NouredineHadjsaïd, “Smart Grids”, Wiley Blackwell 5. Peter S. Fox Penner, “Smart Power: Climate Changes, the Smart Grid, and the Future ofElectric Utilities”, Island Press; 1 edition 8 Jun 2010 6. S. Chowdhury, S. P. Chowdhury, P. Crossley, “Microgrids and Active DistributionNetworks.” Institution of Engineering and Technology, 30 Jun 2009 7. Stuart Borlase, “Smart Grids (Power Engineering)”, CRC Press | |
Essential Reading / Recommended Reading 1. Andres Carvallo, John Cooper, “The Advanced Smart Grid: Edge Power DrivingSustainability: 1”, Artech House Publishers July 2011 2. James Northcote, Green, Robert G. Wilson “Control and Automation of Electric PowerDistribution Systems (Power Engineering)”, CRC Press 3. MladenKezunovic, Mark G. Adamiak, Alexander P. Apostolov, Jeffrey George Gilbert“Substation Automation (Power Electronics and Power Systems)”, Springer 4. R. C. Dugan, Mark F. McGranghan, Surya Santoso, H. Wayne Beaty, “Electrical PowerSystem Quality”, 2nd Edition, McGraw Hill Publication 5. Yang Xiao, “Communication and Networking in Smart Grids”, CRC Press. | |
Evaluation Pattern Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) End Semester Examination(ESE) : 50% (50 marks out of 100 marks) Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II: Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/ Innovative assignments/ presentations/ publications : 10 marks Attendance : 05 marks Total : 50 marks Mid Semester Examination (MSE): Theory Papers: The MSE is conducted for 50 marks of 2 hours duration. Question paper pattern; Five out of Six questions have to be answered. Each question carries 10 marks End Semester Examination (ESE): The ESE is conducted for 100 marks of 3 hours duration. The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution. Question paper pattern is as follows. Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year The criteria for drawing the questions from the Question Bank are as follows 50 % - Medium Level questions 25 % - Simple level questions 25 % - Complex level questions | |
HS521 - PROJECT MANAGEMENT AND FINANCE (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course develops the competencies and skills for planning and controlling projects and understanding interpersonal issues that drive successful project outcomes. Focusing on the introduction of new products and processes, it examines the project management life cycle, defining project parameters, matrix management challenges, effective project management tools and techniques, and the role of a Project Manager. This course guides students through the fundamental project management tools and behavioral skills necessary to successfully launch, lead, and realize benefits from projects in profit and non-profit organizations. |
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Course Outcome |
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CO1: Apply the concept of project management in engineering field through project management life cycle. {L2}{PO9,PO11} CO2: Analyze the quality management and project activity in engineering field through work breakdown structure. {L2}{PO11} CO3: Analyze the fundamentals of project and network diagram in engineering and management domain through PDM techniques. {L3}{PO11} CO4: Understand the basics of Business finance and its applications. {L2}{PO11} CO5: Understand the meaning and approached to Capital and Financial Structure. {L2}{PO11} |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION TO PROJECT MANAGEMENT
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Introduction to Organisations, Principles of Management - its functions, Skills, Organisation Structure, Financial Feasibility. Introduction to Project, Concept, Project Management, Project Life Cycle, Role of Project Manager - Functional Areas, Qualities and Responsibilities, Impact of Delays in Project Completions. | |
Unit-2 |
Teaching Hours:9 |
PROJECT PLAN
|
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Project management functions - Controlling, directing, project authority, responsibility, accountability, Scope of Planning, Market Analysis, Demand Forecasting, Product line analysis, Product Mix Analysis, New Product development, Plant location, plant capacity, Capital Budgeting, Time Value of Money, Cash flow importance, decision tree analysis. | |
Unit-3 |
Teaching Hours:9 |
PROJECT SCHEDULING
|
|
Introduction, Estimation of Time, Project Network Analysis - CPM and PERT model, Gantt Chart, Resource Loading,Resource Leveling, Resource Allocation. Estimating activity time and total program time, total PERT/CPM planning crash times, software‘s used in project management. | |
Unit-4 |
Teaching Hours:9 |
PROJECT MONITORING AND CONTROLLING
|
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Introduction, Purpose, Types of control, Designing and Monitoring Systems, reporting and types. Financial Control, Quality Control, Human Resource Control, Management Control System, Project Quality Management, Managing Risks. | |
Unit-5 |
Teaching Hours:9 |
PROJECT EVALUATION AND AUDITING
|
|
Types of Project Closures, Wrap-Up closure activities, Purpose of Project Evaluation - Advantages, factors considered for termination of project, Project Termination process, Project Final report. Budgeting, Cost estimation, cost escalation, life cycle cost. Project finance in the roads sector, Project finance (Build Own Operate (BOO) / Build Own Operate Transfer (BOOT) Projects / Build Operate and Transfer (BOT). | |
Text Books And Reference Books: Text Books: T1. “Effective Project Management”, Robert K. Wysocki, Robert Beck. Jr., and David B. Crane; - John Wiley & Sons 2003. T2. . Richard A.Brealey, Stewart C.Myers, and Mohanthy, Principles of Corporate Finance, Tata McGraw Hill, 11th Edition, 2014. | |
Essential Reading / Recommended Reading . | |
Evaluation Pattern CIA - 50% out of 100 ESE - 50% out of 100 | |
IC521 - CONSTITUTION OF INDIA (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:0 |
Course Objectives/Course Description |
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This course is aimed to create awareness on the rights and responsibilities as a citizen of India and to understand the administrative structure, legal system in India. |
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Course Outcome |
|
CO1: Explain the fundamental rights granted to citizens of India as per the Constitution CO2: Describe the Directive Principles of State Policy along with its key aspects CO3: Explain the legislative powers of Union Government and its elected legislature CO4: Understand the Indian judiciary with respect to civil and criminal aspects CO5: Explain the working of state government and its electoral powers
|
Unit-1 |
Teaching Hours:6 |
Making of the Constitution and Fundamental Rights
|
|
Introduction to the constitution of India, the preamble of the constitution, Justice, Liberty, equality, Fraternity, basic postulates of the preamble Right to equality, Right to freedom, Right against exploitation, Right to freedom of religion, Cultural and educational rights, Right to constitutional remedies
| |
Unit-2 |
Teaching Hours:6 |
Directive Principles of State Policy and Fundamental Duties
|
|
Directive Principles of State Policy, key aspects envisaged through the directive principles, Article 51A and main duties of a citizen in India | |
Unit-3 |
Teaching Hours:6 |
Union Government and Union Legislature
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|
the president of India, the vice president of India, election method, term, removal, executive and legislative powers, prime minister and council of ministers, election, powers, parliament, the Upper House and the Lower House, composition, function | |
Unit-4 |
Teaching Hours:6 |
Indian Judiciary
|
|
Supreme court, high courts, hierarchy, jurisdiction, civil and criminal cases, judicial activism | |
Unit-5 |
Teaching Hours:6 |
State Government and Elections in India
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|
State executive, governor, powers , legislative council and assembly, composition, powers, electoral process, election commission, emergency | |
Text Books And Reference Books: R1. B R Ambedkar, ‘The Constitution of India’. Government of India R2. Durga Das Basu, Introduction to the Constitution of India, LexisNexis, 24th edition | |
Essential Reading / Recommended Reading - | |
Evaluation Pattern As per university norms | |
IT541E01 - UNIX AND SHELL PROGRAMMING (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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|
|
Course Outcome |
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CO1: . |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
|
|
General Overview of the System: System structure, user perspective, O/S services assumption about Hardware, The Kernel and buffer cache architecture of Unix O/S, System concepts, Kernel data Structure, System administration, Buffer headers, Structure of the buffer pool, Scenarios for retrieval of the buffer, Reading and writing disk block, Advantage and disadvantage of buffer cache. | |
Unit-2 |
Teaching Hours:9 |
INTERNAL REPRESENTATION OF FILES
|
|
Internal Representation of Files: Inodes, Structure of regular, Directories conversions of a path name to an inode, Super block, Inode assignment to a new file, Allocation of disk blocks, Open read write file and record close, File creation, Operation of special files change directory and change root, change owner and change mode. STAT and FSTAT, PIPES mounting and unmounting files system, Link Unlink | |
Unit-3 |
Teaching Hours:9 |
STRUCTURES OF PROCESSES AND PROCESS CONTROL
|
|
Structures of Processes and process control: Process states and transitions layout of system memory, the context of a process, manipulation of process address space, Sleep process creation/termination. The user Id of a process, changing the size of a process. Killing process with signals, job control, scheduling commands: AT and BATCH, TIME, CORN. | |
Unit-4 |
Teaching Hours:9 |
INTRODUCTION TO SHELL SCRIPTS
|
|
Introduction to shell scripts: shell Bourne shell, C shell, Unix commands, permissions, editors, grep family, shell variables, scripts, metacharacters and environment, if and case statements, for while and until loops. Shell programming. | |
Unit-5 |
Teaching Hours:9 |
INTRODUCTION OF AWK AND PERL PROGRAMMING
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|
Introduction of AWK and Perl Programming: AWK pattern scanning, BEGIN and END patterns, AWK arithmetic and variables, and operators, functions, perl; the chop() function, variable and operators. Networking tools: Resolving IP addressing, TELNET, FTP, Socket programming, introduction of Linux structure. | |
Text Books And Reference Books: Text Books: 1. Sumitabha Das “Unix concepts and Applications”, Tata McGraw Hill, Fourth Edition, 2017. 2. Y.Kanetkar “Unix shell programming”, BPB Pub. 3. M.J. Bach “Design of UNIX O.S.", PHI Learning. | |
Essential Reading / Recommended Reading Reference Books: 1. B.W. Kernighan & R. Pike, “The UNIX Programming Environment”, PHI Learning. 2. S.Prata “Advanced UNIX: A Programming's Guide”, BPB Publications, New Delhi. 3. Beck “Linux Kernel, Pearson Education, Asia. | |
Evaluation Pattern CIA - 50% out of 100 ESE - 50% out of 100 | |
NCCOE1 - NCC1 (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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· This Course is offered for cadets of NCC who have successfully completed their B- Certificate. · This Course is offered for the NCC cadets in the Open Elective course offered by the department during the 5th Semester. · This course can be selected if and only if the cadet Successfully Completes the ‘B’- Certificate exam that is conducted centrally oraganized by the NCC Directorate. |
|
Course Outcome |
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CO1: . |
Unit-1 |
Teaching Hours:9 |
Introduction to NCC
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The NCC- Aims, Objectives and Org of NCC-Incentives-Duties of NCC Cadet- NCC Camps: Types and Conduct. National Integration- Importance and Necessity- Factors affecting National Integration- Unity in Diversity. | |
Unit-2 |
Teaching Hours:9 |
Drill
|
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Fundamentals of Foot Drill- Word of Command-Sizing- Salute- Basic Movements – Marching. Fundamentals of Rifle Drill - Basic Movements- Introduction to .22 Rifle- Handling of .22 Rifle- Range procedure and Theory of grouping. | |
Unit-3 |
Teaching Hours:9 |
Social Services
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Social Services-Community Development - Swachh Bharat Abhiyan - Social Service Capsule- Basics of Social Service- Rural Development Programmes- NGO’s. | |
Unit-4 |
Teaching Hours:9 |
Personality Development
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Factors in personality Development- Self-Awareness-Empathy - Critical and Creative Thinking - Decision Making and Problem Solving- Communication Skills- Public Speaking- Group Discussions. | |
Unit-5 |
Teaching Hours:9 |
Disaster Management, Health and Hygiene
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Organization - Types of Disasters - Essential Services Assistance - Civil Defense Organization - Natural Disasters- Man Made Disasters- Firefighting -Hygiene and Sanitation (Personal and Camp)- First Aid in Common Medical Emergencies and Treatment of Wound. | |
Text Books And Reference Books: 1.Airwing Cadet Handbook, Specialized Subject SD/SW, Maxwell Press, 2016. 2. Airwing Cadet Handbook, Common Subject SD/SW, Maxwell Press, 2015. | |
Essential Reading / Recommended Reading 1.Airwing Cadet Handbook, Specialized Subject SD/SW, Maxwell Press, 2016. 2. Airwing Cadet Handbook, Common Subject SD/SW, Maxwell Press, 2015. | |
Evaluation Pattern 1. The assessment will be carried out as overall internal assessment at the end of the semester for 100 marks based on the following.
· Each cadet will appear for ‘B’ Certificate exam which is centrally conducted by the Ministry of Defense, NCC directorate. The Total marks will be for 350. · Each cadets score will be normalized to a maximum of 100 marks based on the overall marks Secured by each cadet. | |
VCSE514 - CCNA: INTRODUCTION TO NETWORKS (ITN) (2021 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:0 |
Course Objectives/Course Description |
|
CCNAv7 teaches comprehensive networking concepts and skills, from network applications to the protocols and services provided to those applications. Learners will progress from basic networking to more complex enterprise and theoretical networking models later in the curriculum. The first course in the CCNA curriculum, Introduction to Networks (ITN) introduces the architectures, models, protocols, and networking elements that connect users, devices, applications and data through the internet and across modern computer networks - including IP addressing and Ethernet fundamentals. The second course, Switching, Routing and Wireless Essentials (SRWE) focuses on switching technologies and router operations that support small-to-medium business networks and includes wireless local area networks (WLANs) and security concepts. |
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Course Outcome |
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CO1: By the end of the course1, Introduction to Networks (ITN), students can build simple local area networks (LANs) that integrate IP addressing schemes, foundational network security, and perform basic configurations for routers and switches. CO2: Students learn key switching and routing concepts. They can perform basic network configuration and troubleshooting, identify and mitigate LAN security threats, and configure and secure a basic WLAN. |
Unit-1 |
Teaching Hours:30 |
CCNAv7: Introduction to Networks (ITN)
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|
Networking Today, Basic Switch and End Device Configuration, Protocols and Models, Physical Layer, Number Systems, Data Link Layer, Ethernet Switching, Network Layer, Address Resolution, Basic Router Configuration, IPv4 Addressing, IPv6 Addressing, ICMP, Transport Layer, Application Layer, Network Security Fundamentals, Build a Small Network | |
Unit-2 |
Teaching Hours:30 |
CCNAv7: Switching, Routing and Wireless Essentials (SRWE)
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Basic Device Configuration, Switching Concepts, VLANs, Inter-VLAN Routing, STP, EthercCannel, DHCPv4, SLAAC and DHCPv6 Concepts, FHRP Concepts, LAN Security Concepts, Switch Security Configuration, WLAN Concepts, WLAN Configuration, Routing Concepts, IP Static Routing, Troubleshoot Static and Default routes. | |
Text Books And Reference Books: 1. https://lms.netacad.com/course/view.php?id=2145156 2. https://lms.netacad.com/course/view.php?id=2144468 3. Introduction to Networks Companion Guide (CCNAv7), By Cisco Networking Academy, Pearson, 2020. 4. Switching, Routing, and Wireless Essentials Companion Guide (CCNAv7), Cisco Press, Hoboken, New Jersey. 2020. | |
Essential Reading / Recommended Reading 1. Behrouz A. Forouzan, “Data communication and Networking”, Tata McGraw-Hill, 2013. 2. James F. Kurose and Keith W. Ross, “Computer Networking: A Top-Down Approach Featuring the Internet”, Pearson Education, 2012. 3. Larry L.Peterson and Peter S. Davie, “Computer Networks”, Fifth Edition, Harcourt Asia Pvt. Ltd., Second Edition, Publishers, 2012. 4. Andrew S. Tanenbaum, “Computer Networks”, 5th Edition, Pearson 2012. 5. William Stallings, “Data and Computer Communication”, Sixth Edition, Pearson Education, 2007.
| |
Evaluation Pattern Online Assessments | |
VCSE516 - FULL STACK WEB DEVELOPMENT (2021 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:0 |
Course Objectives/Course Description |
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This comprehensive Full Stack Java Development course is designed to equip students with the skills and knowledge needed to become proficient in building robust and dynamic web applications. Participants will gain expertise in both front-end and back-end development using Java-based technologies and popular frameworks. The course emphasizes practical hands-on experience through projects and exercises, allowing students to develop real-world applications |
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Course Outcome |
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-: By the end of the course, students can demonstrate a strong understanding of core Java concepts, including object-oriented programming, data types, variables, and control structures. Create responsive and interactive user interfaces using HTML, CSS, and JavaScript. Use front-end libraries and frameworks like React or Angular to build dynamic web pages. Build server-side applications using Java technologies such as Spring. Implement RESTful APIs for communication between the front-end and back-end components. |
Unit-1 |
Teaching Hours:30 |
Core Java
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Declaration and Access Control, Object Orientation, Operators, Interface, Maven Fundamentals, String, Generics and Collections, Stream API's, Layered Architecture. | |
Unit-2 |
Teaching Hours:30 |
Spring, Spring Boot and Angular
|
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Spring Core Introduction / Overview, Spring Container, Dependency Injection, Metadata / Configuration, SPRING BOOT Introduction, Spring Data JPA, Spring Data REST. HTML5, CSS3, BootStrap, Introduction to Angular Framework, Essentials of Angular, Templates, Styles & Directives, Pipes, Services & Dependency Injection, Template-Driven and Reactive Forms, Components Deep Dive / Routing, Http Requests / Observables. | |
Text Books And Reference Books:
| |
Essential Reading / Recommended Reading
| |
Evaluation Pattern Project | |
BTGE631 - CORPORATE SOCIAL RESPONSIBILITY (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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This course will familiarize the students with the concept of corporate social responsibility. The evolution of CSR has far reaching consequences on the development sector in India. The collaboration of companies and NGOs with the community has initiated a new paradigm of change in the country. The students will have an overview of the theories and the frameworks developed in the area of CSR. The paper will discuss a few prominent case studies of CSR. Course Objectives
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Course Outcome |
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CO1: The students will be able to demonstrate their understanding in general on CSR. CO2: To exhibit their skill in executing the responsibilities and implementing different approaches in CSR. CO3: The students will be able to critically evaluate the CSR programs of a corporate |
Unit-1 |
Teaching Hours:7 |
Corporate social responsibility
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Defining CSR. Aim and Objectives, Components of CSR, key drivers, History and Evolution of CSR in the Indian and international context, CSR policies and Governance, Laws and Regulations. Competencies of CSR Professionals. | |
Unit-2 |
Teaching Hours:7 |
Stakeholder Engagement
|
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Stakeholder engagement, Interaction in a Multi-Stakeholder Context: CSR role on internal environment: Employees, Human Resource Management - labour security and human rights, Health and Safety.CSR role on External environment: 1) Customers: Consumer rights and movements affecting CSR; (2) Community: Community involvement, (3) Shareholders (4) Suppliers. | |
Unit-3 |
Teaching Hours:6 |
CSR towards Environment and Biodiversity
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Environment: Need for Environmental assessments. Governments’ response to CSR. Role of Biodiversity, Climate change and Environment in business. Environmental compliance. | |
Unit-4 |
Teaching Hours:4 |
Sustainability models
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Benefits of CSR to Business. Factors hindering CSR activities in companies | |
Unit-5 |
Teaching Hours:6 |
Theories of CSR
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Theories of CSR: A.B Carroll, Wood, and stakeholders Theories. The triple bottom line approach. Stakeholder engagement, Standards and Codes – SA 8000, the Global Compact, GRI, ISO 26000. | |
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern CIA 1 - 20 Marks CIA 2 - 50 Marks CIA 3 - 20 marks
ESE - 100 marks | |
BTGE632 - DIGITAL MEDIA (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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This course provides students the insight on search engine optimization, social media and digital marketing techniques that helps them understand how each of the social media platforms works and how to strategize for any type of objectives from clients. Students will discover the potential of digital media space and will have hands on experience with different digital platforms. |
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Course Outcome |
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CO1: Understand search engine optimization (SEO) techniques and principles. CO2: Gain expertise in managing and marketing on various social media platforms. CO3: Apply digital marketing techniques to achieve specific business objectives.
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Unit-1 |
Teaching Hours:10 |
Concepts
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Website Hosting/Design/Development/Content, Fundamentals of SEO, Voice Search Optimization, Local SEO, Advanced/Technical SEO, SEO Audit, Competition Analysis, Concepts of Digital Marketing | |
Unit-2 |
Teaching Hours:10 |
Marketing
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Marketing on platforms – Facebook/Twitter/LinkedIn/Instagram/YouTube, Quora, Basics of Video Editing, Inbound Marketing, Email Marketing, Digital Marketing Planning and Strategy, Marketing Automations and Tools | |
Unit-3 |
Teaching Hours:10 |
Growth Hacking
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Ethical vs. Unethical, Funnels, KPI’s, Viral Coefficient, Cohorts, Segments, Multivariate Testing, Lifetime Value of a Customer, Customer Acquisition Cost, Analytics Types, Tools, Project | |
Text Books And Reference Books: Phillip J. Windley, "Digital Identity" O'Reilly Media, 2005 | |
Essential Reading / Recommended Reading Dan Rayburn, Michael Hoch, "The Business of Streaming and Digital Media", Focal Press, 2005 | |
Evaluation Pattern
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BTGE633 - FUNCTIONAL ENGLISH (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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Students will be able to develop a clear understanding of the principles and characteristics of communication in professional settings. They would have developed skills for grammatical accuracy, precise vocabulary, clear style and appropriate tone for formal, professional communication |
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Course Outcome |
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1: Upon completing the syllabus students will be able to show a good grasp of the fundamentals of English language.
Students will be able to deliver the topic orally and in writing with greater independence and greater linguistic correctness
2: Will be able to distinguish and discuss differences in English language structure between speech and writing as well as distinguish and discuss stylistic differences (formal and informal English) 3: Will be able to actively and independently participate in group discussions, can make successful attempt to persuade in decision making, and can withstand the pressures in interview. 4: Will be equipped to network in academic and work settings. Would be able to confidently appear in front of a larger crowd and give presentations 5: Will acquire skills in CV writing, cover letter writing and content generation |
Unit-1 |
Teaching Hours:6 |
Verbal
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● Training on Nouns, Pronouns, Homophones, Homonyms ● Verbs and Gender ● Training on Tenses ● Active Voice, Passive Voice and Sentence Formation ● Direct and Indirect Speech ● Adjectives and Adverbs | |
Unit-2 |
Teaching Hours:6 |
FORMAL COMMUNICATION
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● Barriers of communication and effective solutions ● Workplace English ● Pleasantries and networking ● Cross-cultural understanding
| |
Unit-3 |
Teaching Hours:6 |
WRITTEN Workplace English
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• Professional Writing • Analytical • Instructional including writing MOMs • Project Planning • Creative writing • Blogging • Event management proposal meeting • Professional communication – Email Etiquette, Cover letters, Resume | |
Unit-4 |
Teaching Hours:6 |
WRITTEN Academic Writing
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● Application in technical fields and written communication ● Project writing, essays and theories ● Paper presentation skills and creative writing ● Final project writing | |
Unit-5 |
Teaching Hours:6 |
PUBLIC SPEAKING
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● Training on Presentation Skills ● Body Language and Accent Training ● Voice projection ● Group Discussion Do’s and Don’ts ● Getting individual feedback Training on appropriate grooming code and body language in a professional workplace and delivery of apt elevator pitch | |
Text Books And Reference Books: TEXT BOOKS ● High School English Grammar and Composition Book, Wren and Martin ● Writing At Work: Professional Writing Skills for People, Edward L. Smith and Stephen A. Bernhardt | |
Essential Reading / Recommended Reading REFERENCE BOOKS ● English grammar in use book – Raymond Murphy ● WordPress to Go: How to Build a WordPress Website on Your Own Domain, from Scratch, Even If You Are a Complete Beginner Sarah McHarry. ● The Art of Public Speaking ● Textbook by Stephen E. Lucas ● True Professionalism, David Maister
| |
Evaluation Pattern Stress Interview/ Panel Discussion/Group | |
BTGE634 - GERMAN (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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Description: Can understand and use familiar, everyday expressions and very simple sentences, which relate to the satisfying of concrete needs. Can introduce him/herself and others as well as ask others about themselves Objectives Impart the language and through that insight into the country and the culture. Sensitize the students to the environment of a foreign country. To enable the students adapt to a new environment and culture. |
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Course Outcome |
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CO1: Can understand and use familiar, everyday expressions and very simple sentences, which relate to the satisfying of concrete needs. CO2: Can introduce oneself and others as well as ask others about themselves ? e.g. where they live, whom they know and what they own ? and can respond to questions of this nature. C03: Can handle everyday situations like shopping, eating out, visiting places, travelling, holidaying, requesting for information, making an appointment, cancelling an appointment, filling up a form etc. |
Unit-1 |
Teaching Hours:6 |
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INTRODUCTION, SELF AND OTHERS
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Introduction: Greeting and saying goodbye, Introducing yourself and others, Talking about yourself and others. Numbers, telephone numbers and mail-addresses, the alphabet (spelling), countries and languages. Question words, sentences, verbs and personal pronouns. | |||||||||||||||||||
Unit-2 |
Teaching Hours:6 |
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AROUND YOU? :FRIENDS, COLLEGEAUS
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Hobbies, meeting friends, Weekdays, months and seasons, work and working times Articles, verbs, Yes/ no questions, Plurals, The verbs “to have” and “to be”. | |||||||||||||||||||
Unit-3 |
Teaching Hours:6 |
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PLACES TO VISIT
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Places in the city, asking for directions, Means of transport. Orientation in a city. Imperative sentences. | |||||||||||||||||||
Unit-4 |
Teaching Hours:6 |
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FOOD
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Shopping for food, conversation during food shopping, ordering food and drinks, general greetings during eating out. Word position in sentence, accusative case. | |||||||||||||||||||
Unit-5 |
Teaching Hours:6 |
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TIME WITH FRIENDS
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Telling time and organizing meetings with family and friends. Making plans, Birthday invitations, in Restaurants. Finding information in a text, event tips in the radio, leisure activities, brochures. Possessive articles, Modal verbs ,simplePast tense (to have and to be) | |||||||||||||||||||
Text Books And Reference Books: · Netzwerk – Deutsch als Fremdsprache A1. Publisher- Langenscheidt | |||||||||||||||||||
Essential Reading / Recommended Reading · Netzwerk – Deutsch als Fremdsprache A1. Publisher- Langenscheidt | |||||||||||||||||||
Evaluation Pattern · CIA I
· CIA II Written examination 50 marks
· CIA III
· SEMESTER EXAM
Written examination 100 marks
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BTGE635 - INTELLECTUAL PROPERTY RIGHTS (2021 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
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Max Marks:100 |
Credits:2 |
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Course Objectives/Course Description |
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Innovation is crucial to us and plays significant role in the growth of economy. Government policies and legal framework offer protection to new inventions and creative works. This course intends to equip students to understand the policies and procedures they may have to rely on for the purposed of protecting their inventions or creative works during the course of their study or employment. The course consists of five units. Theories behind the protection of intellectual property and its role in promoting innovations for the progress of the society are the focus of first unit. Second unit deals with protection of inventions through patent regime in India touching upon the process of obtaining international patents. The central feature of getting patent is to establish new invention through evidence. This is done through maintaining experimental/lab records and other necessary documents. The process of creating and maintain documentary evidence is dealt in Unit 3. Computers have become an integral part of human life. Till 1980, computer related inventions were not given much importance and lying low but today they have assumed huge significance in our economy. Computer related inventions and their protection which requires special treatment under legal regimes are discussed in Unit 4. The last module deals with innovations in e- commerce environment.
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Course Outcome |
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CO1: Understand the meaning and importance of
intellectual property rights as well as different
categories of intellectual property. CO2: Understand the meaning of patentable invention,
the procedure for filing patent applications, rights of
the patentee and the different rights of patentee. CO3: Maintain research records in the patent process, the
process of patent document searching and how to
interact with patent agent or attorney. CO4: Understand the issues related to patenting of
software, digital rights management and database
management system. CO5: Understand the intellectual property issues in e-
commerce, evidentiary value of electronic signature
certificates, protection of websites and the protection
of semiconductor integrated circuits. |
Unit-1 |
Teaching Hours:6 |
Introduction
|
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Detailed Syllabus: Philosophy of intellectual property - Intellectual Property & Intellectual Assists – Significance of IP for Engineers and Scientists – Types of IP – Legal framework for Protection of IP – Strategies for IP protection and role of Engineers and Scientists. | |
Unit-2 |
Teaching Hours:6 |
Patenting Inventions
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Meaning of Invention – Product and Process Patents – True inventor – Applications for Patent – Procedures for obtaining Patent – Award of Patent – rights of patentee – grounds for invalidation – Legal remedies – International patents | |
Unit-3 |
Teaching Hours:6 |
Inventive Activities
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|
Research Records in the patent process – Inventorship - Internet patent document searching and interactions with an information specialist - Interactions with a patent agent or attorney - Ancillary patent activities - Technology transfer, patent licensing and related strategies. | |
Unit-4 |
Teaching Hours:6 |
Computer Implemented Inventions
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Patents and software – Business Method Patents – Data protection – Administrative methods – Digital Rights Management (DRM) – Database and Database Management systems - Billing and payment – Graphical User Interface (GUI) – Simulations – E-learning – Medical informatics – Mathematical models | |
Unit-5 |
Teaching Hours:6 |
Innovations in E-Commerce
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|
IP issues in e-commerce - Protection of websites – website hosting agreements – Copyright issues – Patentability of online business models – Jurisdiction – Digital signatures – Evidentiary value of Electronic signature certificates – Role of Certifying Authorities – Protection of Semiconductor ICs | |
Text Books And Reference Books: 1. V.J. Taraporevala’s, Law of Intellectual Property, Third Edition, 2019 2. Elizabeth Verkey, Intellectual Property, Eastern Book Company, 2015 | |
Essential Reading / Recommended Reading 1. Martin Adelman, Cases and Materials on Patent Law, 2015 2. Avery N. Goldstein, Patent Law for Scientists and Engineers, Taylor & Francis (2005) | |
Evaluation Pattern CIA 1 Assignment description: Class test to identify the different aspects of IP.
Assignment details: MCQs
CIA II (MSE) Assessment Description: Closed book exam Assignment Details: Mid semester examination five questions need to be answered.
CIA III Assessment Description: Students would be assessed on the understanding of the different forms of IP, relevant theoretical justifications of intellectual property protection and the relevant IP statute from practitioner’s approach taught in the class and their ability to apply it correctly to the given problem and proposing solutions.
Assignment details: Students will be given a hypothetical legal problem in IP and will be required to write short essay, containing maximum 500 words. In the short essay, they have to answer the following questions 1. Identify the appropriate form of intellectual property. 2. Describe whether a pertinent theoretical justification meets or does not meet the respective form of IP. 3. Apply the correct principle of IP protection to the given case. 4. Evaluate the lacunae in the existing IP mechanism in comparison to international framework. 5. Devise a correct way of handling the lacunas. ESE DETAILS - Assessment Description : Closed book exam Assignment Details: Five problem based questions need to be answered out of seven questions. | |
BTGE636 - INTRODUCTION TO AVIATION (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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A student successfully completing this course will be able to: Explain basic terms and concepts in air transportation, including commercial, military, and general aviation; air traffic control. Identify on the parts of an aircraft, classify the aircraft types and Construct models of an Aircraft. Understand the types of Aero engines and analyse the impact of meteorology in Aviation. |
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Course Outcome |
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CO1: Interpret the fundamental principles of flight based on theorems and parts of the Aircraft CO2: Summarize the types of aircrafts and illustrate modelling of an Aircraft CO3: Identify the types of Aero engines and Make use of Meteorology |
Unit-1 |
Teaching Hours:10 |
Introduction to Principles of Flight
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|
Development of Aviation- Introduction- Laws of Motion -Bernoulli’s Theorem and Venturi Effect – Aero foil- Forces on an Aircraft- Flaps and Slats- Stalling- Thrust, Basic Flight Instruments- Introduction of Radar- Requirement of Navigation | |
Unit-2 |
Teaching Hours:10 |
Aircrafts and Aeromodelling
|
|
Airfield Layout- Rules of the Air- Circuit Procedure ATC / RT Procedure Aircraft Controls- Fuselage – Main Tail Plane Ailerons- Elevators- Rudder –Landing Gear. Fighters- Transports- Helicopters- Foreign Aircraft History of Aero modelling- Materials used in Aero modelling - Types of Aero models | |
Unit-3 |
Teaching Hours:10 |
Aero Engines and Meteorology
|
|
Introduction of Aero engines - Types of Engines-Piston Engines -Jet Engines – Turboprop Engines, Importance of Meteorology in Aviation- Atmosphere - Clouds and Precipitation - Visibility – Humidity and Condensation | |
Text Books And Reference Books: Text Books: • Airwing Cadet Handbook, Specialized Subject SD/SW, Maxwell Press, 2016. • Introduction to Aerospace Engineering: Basic Principles of Flight, Ethirajan Rathakrishnan, Wiley Press, 2021.
| |
Essential Reading / Recommended Reading Reference Books: • An Observer’s Guide to Clouds and Weather, Toby Carlson, Paul Knight, and Celia Wyckoff,2015, American Meteorological Society. • Aero Engines, LNVM Society, 2007, L.N.V.M. Society Group of Institutes. | |
Evaluation Pattern This Course do not have CIA 1/2/3. It has Overall CIA(out of 100 and will be Converted to 50) and ESE ( out of 100 and will be converted to 50). Total Marks=100. | |
BTGE637 - PROFESSIONAL PSYCHOLOGY (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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1. To understand various developmental changes that take place in human life and how people's thoughts, feelings, and behaviors are influenced by the social context consisting of actual, imagined, or implied presence of others. 2. To develop interpersonal awareness and skills, especially in the context of diversity and difference 3. To develop the psychosocial skills required in the professional world
4. To introduce the students to the existing theory and research in the past and contemporary social settings comprising viz, the intra-individual, inter-individual, and social factors that influence individual and group behavior. |
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Course Outcome |
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CO1: Understand the frameworks for the psychology of human development. CO2: Show greater awareness of their thinking styles, relational styles and behavioral styles of
functioning
CO3: Develop interpersonal awareness and skills, especially in the context of diversity and
difference
CO4: Develop preparatory skills toward effective work-life balance CO5: Develop an overall understanding of the psychosocial skills required in professional world |
Unit-1 |
Teaching Hours:7 |
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Introduction to Psychological Theories
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Psychosocial development (Erickson)-Development of Cognition (Piaget)-Moral Development (Kohlberg)-Faith Development (Fowler) | ||||||||||||||||
Unit-2 |
Teaching Hours:8 |
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Self-Awareness and Analysis
|
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Thinking Styles (Cognitive distortions)- Interpersonal relationship styles (adult attachment theories)- Personality styles (Jung type indicator or Myers Briggs Type Indicator)- Coping styles: Emotion-focused and Problem-focused Analysis: Self-Analysis – Analyzing others-Body language –Facial expressions | ||||||||||||||||
Unit-3 |
Teaching Hours:7 |
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Social Influences
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Conformity: Asch’s Research on Conformity-Factors Affecting Conformity; Compliance -The Underlying Principles - Ingratiation;Obedience to Authority-Destructive Obedience | ||||||||||||||||
Unit-4 |
Teaching Hours:8 |
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Approaches to work motivation and job design
|
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Overview of motivation - Need theories - Expectancy theory – Justice and citizenship theories - Goal-setting theory - Goals and self -regulation - Self-concept and individual differences in motivation - Pay and motivation - Motivation through job redesign
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Text Books And Reference Books: Baron, R. A., (2012), Psychology, 5th edition. Pearson Education India Baron, R. A., & Branscombe, N. R. (2006). Social psychology. Pearson Education India. Nelson Goud and Abe Arkoff (2005), Psychology and Personal Growth, Edition, Allyn and Bacon. | ||||||||||||||||
Essential Reading / Recommended Reading Nelson Jones. (2006), Human Relationship skills: Coaching and self-coaching, 4th edition, Routledge. | ||||||||||||||||
Evaluation Pattern
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BTGE651 - DATA ANALYTICS THROUGH SPSS (2021 Batch) | ||||||||||||||||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
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Max Marks:100 |
Credits:2 |
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Course Objectives/Course Description |
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Course Description Course objectives After the completion of the course, you should be able to:
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Course Outcome |
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CO1: Students will understand the concepts involved for analyzing Business data CO2: Students will be able to understand how to use software like SPSS to analyse data CO3: Students will be able to appreciate the use of Data Analytics for business decision making |
Unit-1 |
Teaching Hours:2 |
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Introduction to data Analysis
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|||||||
Introduction to Statistics and SPSS package viz.,, Types of data, data editing, coding, cleaning, outliers, missing data, import, export, data labeling, transforming data. | |||||||
Unit-2 |
Teaching Hours:2 |
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Data Visualization
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Graphs, scatter plot, charts, frequency tables, histogram, Boxplot, pie chart, etc | |||||||
Unit-3 |
Teaching Hours:4 |
||||||
Descriptive Statistics and Hypothesis testing
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Basic statistics like mean, median, mode, SD, Examine relationship between variables example correlation, regression, etc., Compare groups to determine if there are significant differences between these groups example T-test, ANOVA etc., and to measure the association/independence using Chi-square., etc. | |||||||
Unit-4 |
Teaching Hours:4 |
||||||
Logistic Regression
|
|||||||
Application of logistic regression in SPSS using case study | |||||||
Unit-5 |
Teaching Hours:4 |
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Factor analysis
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|||||||
Application of factor analysis in SPSS using case study | |||||||
Unit-6 |
Teaching Hours:14 |
||||||
Cluster Analysis and Discriminant analysis
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|||||||
Application of Cluster analysis and Discriminant in SPSS using case study | |||||||
Text Books And Reference Books:
1. Andy field, “Discovering Statistics Using SPSS”, SAGE Publications, Second Edition, 2006.
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Essential Reading / Recommended Reading
1. Darren George|Paul Mallery, “SPSS for Windows Step by Step”, Pearson, Tenth Edition, 2012.
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Evaluation Pattern
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BTGE652 - DIGITAL MARKETING (2021 Batch) | |||||||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
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Max Marks:100 |
Credits:2 |
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Course Objectives/Course Description |
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Course Description:
Developing a successful digital marketing strategy and implementation is both an art and science. It involves in-depth knowledge of dynamics of new media (Social Media, Mobile) and utilizing the right resources and marketing skills to design and launch successful customer engagement campaigns. Digital Marketing course has been designed to help students to understand both functional and management roles required to plan and execute effective Digital Marketing campaigns. The course also helps students gain an insight how to plan and implement Digital Marketing initiatives
Course Objectives:
· To apply the basics of digital marketing in the contemporary business scenario
· To utilize google ads for promotional activities
· To contrast various social media marketing platforms and activities
· To analyse the search engine optimization and search engine marketing strategies To explain analytics pertaining to digital marketing initiatives
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Course Outcome |
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CO1: Plan a digital marketing campaign as per client requirements CO2: Apply google ads in digital campaigns CO3: Analyse the appropriateness of social media marketing strategies with respect to campaign objectives CO4: Examine the search engine optimization efforts CO5: Appraise the digital marketing analytics related to the project |
Unit-1 |
Teaching Hours:5 |
Introduction to Digital Marketing
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Digital Marketing: Origin of digital marketing; Traditional Vs Digital Marketing; Internet Users in India; Grehan’s 4Ps of digital marketing; The consumer decision journey; The P-O-E-M Framework; The digital landscape; Digital Marketing Plan. Ethical Challenges: Frauds on the Web, Data and Identity Theft, Issue of Privacy. Information Technology Act, 2000. | |
Unit-2 |
Teaching Hours:6 |
Search Engine Marketing
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Why pay for Search Advertising? Understanding Ad Placement; Understanding Ad ranks; Creating the first Ad campaign; Enhancing the Ad campaigns; Performance reports. Google Adsense. Concept of Display Advertising; Types of display Ads; Buying Models; Display Plan; Targeting – Contextual targeting- Placement Targeting-Remarketing- Interest categories- Geographic Language Tagging; What makes a good Ad? Programmatic digital advertising; Analytics tools – viewability, on target reach, Ad fraud, Brand Health. | |
Unit-3 |
Teaching Hours:9 |
Social Media Marketing
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|
How to build a successful social media strategy? Facebook Marketing- Facebook for Business-Anatomy of an Ad campaign – Adverts - Facebook Insights
Linkedin Marketing – Linkedin Strategy- Sales lead generation – Content Strategy – Linkedin Analytics – Targeting – Ad Campaign
Twitter Marketing – Getting started with Twitter – Building a content strategy – Twitter Ads – Twitter Analytics Instagram Marketing – Objectives – Content Strategy – Style guidelines – Hashtags – Videos- Sponsored Ads – Apps – Generate leads | |
Unit-4 |
Teaching Hours:6 |
e-mail Marketing and Search Engine Optimisation
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e-mail Marketing – Building a List- Content Strategies – e-mail newsletter – Automating e-mail marketing- Analytics. Search Engine Optimisation – How search engine works? SEO Phases; On page Optimisation; Off-page Optimisation; Social Media Reach; Maintenance | |
Unit-5 |
Teaching Hours:4 |
Mobile Marketing and Web Analytics
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Mobile Advertising – Mobile Marketing toolkit – Mobile Marketing Features – Mobile Analytics Web Analytics – Key Metrics – Making web analytics actionable – Types of tracking codes | |
Text Books And Reference Books: 1. Seema Gupta. (2020). Digital Marketing (2nd Ed). Tata Mc Graw Hill | |
Essential Reading / Recommended Reading
1. Kerpen, D., Berk, R., Greenbaum, M. (2019). Likeable social media, Third Edition: How To Delight Your Customers, Create an Irresistible Brand, & Be Generally Amazing On All Social Networks That Matter. United Kingdom: McGraw-Hill Education.
4. Marshall, P., Rhodes, M., Todd, B. (2020). Ultimate Guide to Google Ads. United States: Entrepreneur Press.
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Evaluation Pattern
CIA 1 – Digital Marketing Plan – 20 Marks
CIA 2 – Google Ads – 10 Marks
CIA 3 – Social Media Marketing – 25 Marks
CIA 4 – Web Analysis (SEO) – 20 Marks
CIA 5 – Analytics – 20 Marks
Attendance – 5 Marks
CIA – Total Marks – 100 Converted to 50
ETE
Viva Voce – 50 Marks
Report – 50 Marks
ETE – 100 Marks – Converted to 50 Overall Marks – CIA + ESE = 100
| |
BTGE653 - DIGITAL WRITING (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
|
The course will develop the knowledge and skills required to write content for digital media. Students will learn how to craft writing for different areas of the media by focusing on genres such as profiles, informative pieces, articles and content pieces. Students will work on pitching and marketing ideas, discuss topics such as timelines, word counts and deadlines. The course will also examine the principles of reporting and the legal and ethical issues associated with content writing
The course intends to provide students with an in-depth understanding of the nature of digital content. The course will acquaint students with the techniques of writing simple but polished digital content. The subject will develop creativity in writing and imaginative approaches to digital content writing. The paper will help students understand the mechanics of content writing |
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Course Outcome |
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CO1: Students will learn how to write digital content for websites, blogs, and general social networking sites CO2: Students will learn the importance of using hyperlinks to information sources when writing an article CO3: Students will be able to differentiate between original and plagiarized content and develop mechanisms to avoid plagiarism |
Unit-1 |
Teaching Hours:6 |
Introduction to Digital Writing
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|
What is online writing, Narrative structure for online and digital stories, writing for university publications, Copyright, Ownership, and authorship, Approach to digital storytelling, Interactive narratives, sourcing information, exploring transmedia stories, data visualization, online identities and the self, alternate realities | |
Unit-2 |
Teaching Hours:6 |
Writing Techniques
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|
Online news writing, headlines, sentences, links, tables and infographics, meaningful linking, effective illustrations, content strategy, message, media, style and tone, purposes, personas and scenarios | |
Unit-3 |
Teaching Hours:6 |
Writing for Newspapers
|
|
Journalistic writing-nature, process and styles, Concept of news-definitions, news values, nose for news, News writing- elements of news stories-Lead, body & closure; 5 Ws & 1 H, News writing structures- pyramid, inverted pyramid, hourglass, chronological, Newspaper design, Anatomy of a newspaper, Typography-font type, anatomy of type, type families, Readability & aesthetic principles, Page layout & design | |
Unit-4 |
Teaching Hours:6 |
Writing a Book Proposal
|
|
Process of book publishing, understanding book proposal, the importance of book proposal, book proposal structure, steps for writing a book proposal, some common mistakes made when writing a book proposal. | |
Unit-5 |
Teaching Hours:6 |
Writing Resume and Cover
|
|
Introduction to resume, the 3Fs of resume writing, parts of a resume, difference between CV and resume, characteristics of a good resume, anatomy of a resume, common mistakes made while writing a resume, introduction to cover letter, writing a cover letter for a job application, writing a cover letter for a book proposal, common mistakes made while writing a cover letter | |
Text Books And Reference Books:
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Essential Reading / Recommended Reading
| |
Evaluation Pattern Introduction - 10 Content - 10 Structure - 10 Clarity- 10 Conclusion -10 | |
BTGE654 - PHOTOGRAPHY (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
|
The course introduces the art of photographic image making and printing. You will learn to see and appreciate light in a new way, learn to see and design shapes in the frame, and you will learn how to make fine prints. In this course, you will learn how to properly expose the camera, how to develop good images, and to make beautiful exhibition prints. This is not merely a technical course however the most important thing you can bring away from this course is a new sense of seeing. To be able to have a finer appreciation of light in its myriad manifestations, to discover meaning in images rather than words, or most importantly, how to make images, important and powerful in their own right, rather than merely “take pictures” is the main goal of this course. |
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Course Outcome |
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CO1: Ability to demonstrate understanding and clarity in content.
Ability to read and interpretate photographs
Ability to demonstrate knowledge of visual design and art. CO2: Ability to demonstrate technical documentation of knowledge attained, process involved.
Ability to read and interpretate photographs
Ability to demonstrate knowledge of visual design and art. CO3: Ability to demonstrate Quality and Comprehensiveness.
Ability to read and interpretate photographs
Ability to demonstrate understanding of material, structure and details and graphical understanding. |
Unit-1 |
Teaching Hours:10 |
Introduction of Photography
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Exposure to a variety of Analog and digital photographic techniques. Basics of shots, sizes, and angles. Technical aspects such as exposure triangle, composition, framing, and introduction to lighting. Printing The enlarger, set up, timer use, enlarging lenses, the test strip, developing procedures, contrast control with variable contrast filters, spotting and matting, archival processing. | |
Unit-2 |
Teaching Hours:8 |
Photographic Design
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Introduction to contemporary and historic photographers and their works. Understanding and applying visual design elements and principles in photography. | |
Unit-3 |
Teaching Hours:8 |
Appreciation of photography
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Multiple photographic practices such as documentary photography, fine art photography and fashion photography, product photography and architecture photography. Moral and theoretical issues attached to the medium, such as photography’s relationships between truth, beauty, and fact, as well as the ethics of war photography. | |
Unit-4 |
Teaching Hours:4 |
Print media and Portfolio
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Introduction to Print medium. Portfolios (Digital Format) | |
Text Books And Reference Books: 1. Schaeffer J. P. (1998) The Ansel Adams guide: Basic techniques of photography, Boston: Little Brown and Company. 2. Horenstein, H. (1977) Beyond Basic Photography: A Technical Manual, Boston: Little Brown and Company.
3. Craven, G. M.(1990) Object and Image: An Introduction to Photography, New Jersey: Prentice-Hall, Englewood Cliffs. | |
Essential Reading / Recommended Reading 1. Peterson, B. (2016) Understanding Exposure, Fourth Edition, Random House USA Inc. 2. DK (2015) Digital Photography Complete Course, DK; Reissue edition. 3. Northrup T. & Northrup C. (2012) Tony Northrup's DSLR Book: How to Create Stunning Digital Photography, (2nd edition) Mason Press. 4. Hunter, F., Biver S. & Fuqua P. (2015) Light Science & Magic: An Introduction to Photographic Lighting, Routledge, ISBN-10: 0415719402.
5. Peterson B. (2017) Understanding Colour in Photography: Using Colour, Composition, and Exposure to Create Vivid Photos, Random House US, ISBN-10 : 9780770433116 | |
Evaluation Pattern The assessment pattern comprises of two components; the Continuous Internal Assessment (CIA) and the End Semester Examination (ESE). The weightage of marks for subjects having both CIA marks, as well as ESE marks, have a ratio of 50:50. CONTINUOUS INTERNAL ASSESSMENT (CIA): 50% Continuous Internal Assessment for this course shall be conducted by the respective faculty in the form of different types of assignments. Students need to complete the assignments within the stipulated time for the award of marks. END SEMESTER EXAMINATION (ESE): 50% Eligibility to appear for ESE is a score of a minimum of 50% in the CIA. PASS CRITERIA A student shall pass the course only on a minimum aggregate score (CIA+ESE) of 45% and a minimum CIA Score of 50% and an ESE score of 40% | |
BTGE655 - ACTING COURSE (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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In this course the students are introduced different aspects of acting such as creating a character, analyzing a script, working on voice and developing body language. At the end of the course the learners will perform a monologue. The course aims at the study and practice of Classical Acting. The development of individual imagination, insight, skills and disciplines in the presentation of drama to audience. |
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Course Outcome |
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• To gain an understanding of acting principles and techniques • Develop skills in the analysis and interpretation of dramatic texts for performance • Explore basic voice and movement skills to create dramatic effect on stage • Understand the basic production processes • To perform a monologue |
Unit-1 |
Teaching Hours:10 |
Unit 1
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Inner characterization: History of acting, First performance,Art representation vs art of experiencing, Characterization and actor’s notebook, Stanislavski’s system, Objective and super-objective, Working with a script
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Unit-2 |
Teaching Hours:10 |
Unit 2
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Outer characterization : Stanislavski’s system., Method of physical actions, Building character’s body language, Building character’s voice,
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Unit-3 |
Teaching Hours:10 |
Unit 3
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Performing a Monologue: Theatrical etude, Working with props, sets, light and costume, Creating atmosphere, Run-through, | |
Text Books And Reference Books: Stanislavsky, Constantine. “An Actor prepares.” | |
Essential Reading / Recommended Reading Stanislavsky, Constantine. “An Actor prepares.” | |
Evaluation Pattern The assessment of the students is happening throughout the course and will be completed with the final monologue performance.
The assignments need to be submitted via Google Classroom by the given deadlines. Actor’s notebooks need to follow the given requirements. Monologues will be performed live.
Completing all the given assignments throughout the course –20 marks Submission of actor’s notebook – 20 marks Final monologue performance – 60 marks | |
BTGE656 - CREATIVITY AND INNOVATION (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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To equip students with skill and aptitude for creativity and innovation through
To stimulate curiosity in students to identify the areas of gaps and opportunities and solutions that can be provided
To stimulate creativity in students to come up with ideas for the areas of gaps and opportunities
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Course Outcome |
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CO-1: Develop an aptitude for creative thinking and problem solving in the areas that drive their interest. CO-2: Understand the benefits of team work and collaborative thinking CO-3: Understand the three keys aspects of the creative process viz. ACES CO-4: Develop projects to understand the various principles and elements of creativity and innovation CO-5: Apply the concepts of IPR to verify the projects which may be patentable, design and copyright protected |
Unit-1 |
Teaching Hours:6 |
Introduction
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Creativity & Innovation, A journey through major breakthrough innovations around the world., Collaborative Creativity | |
Unit-2 |
Teaching Hours:6 |
The Creative Process Part I (Analyzing Problems)
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Analyzing Problems (Smart Storming), Theory and practice, Rethinking Thinking Imagination Observing, Abstracting, Recognizing Patterns, Forming Patterns | |
Unit-3 |
Teaching Hours:6 |
The Creative Process Part II (Creating Ideas)
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Creative Thinking Techniques and Methods, Body Thinking, Empathizing (Design Thinking),
Dimensional Thinking Evolution and Evaluation of Ideas through design Thinking | |
Unit-4 |
Teaching Hours:6 |
The Creative Process Part III (Engineering Solutions)
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Proof of Concept, Minimum Viable Proposition, Rapid Iteration Process | |
Unit-5 |
Teaching Hours:6 |
Innovation and IPR
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Patents, Designs, Copyrights, Geographical Indications, Trademarks, Trade Secret | |
Text Books And Reference Books: Activity Based Teaching. No text books and reference books | |
Essential Reading / Recommended Reading Activity Based Teaching. No text books and reference books | |
Evaluation Pattern This course consists of Overall Cia for 100 marks. No End Semester Examination for this course. | |
BTGE657 - PAINTING AND SKETCHING (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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The course will develop the skills required to represent elements of nature and surrounding objects. Students will learn how to use the appropriate medium for representing their thought process. The course will examine the representation skills through exercises on sketching and rendering. |
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Course Outcome |
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CO3: Students will learn how to represent their ideas and thought processes diagrammatically through sketching and rendering. |
Unit-1 |
Teaching Hours:10 |
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Representation through Sketching
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This unit will look at sketching as a medium to represent ideas and thought processes. Freehand Drawing Techniques, Landscape drawing . | ||
Unit-2 |
Teaching Hours:10 |
|
Introduction to Watercolour Painting Techniques
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Execute simple exercises in Collages to understand Flat Wash, Graded Wash, Wet on Dry, Wet on Wet. Techniques of Blooming, Splattering, Sponging will be used as a medium of representation. Study of brush strokes as a finish.How | ||
Unit-3 |
Teaching Hours:10 |
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Introduction to Soft Pastel Techniques
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To create simple elements in nature Plants, Different types of Trees,water bodies in architecture. etc. | ||
Text Books And Reference Books: Drawing : (Ching, Francis D K)
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Essential Reading / Recommended Reading milind mulick watercolor sketchbook by milind mulick
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Evaluation Pattern The following courses do not | ||
BTGE658 - DESIGN THINKING (2021 Batch) | ||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
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Max Marks:100 |
Credits:2 |
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Course Objectives/Course Description |
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Course Description: Throughout the course students will work on three different challenges; one focused on product design, one focused on service design and one focused on systems or business design. By starting with a very tangible challenge around product design, students will be able to hone their skills in the process before moving into more complex challenges around business and systems level design.
The course will be teamwork-oriented, but students will also complete readings and independent activities that support the group work and ensure individual depth of knowledge.
Course objectives: l Expose students to the design process as a tool for innovation. l Develop students’ professional skills in client management and communication. l Demonstrate the value of developing a local network and assist students in making lasting connections with the business community. l Students develop a portfolio of work to set them apart in the job market. l Provide an authentic opportunity for students to develop teamwork and leadership skills. |
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Course Outcome |
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CO1: Design Process
1. Students develop a strong understanding of the Design Process and how it can be applied in a variety of business settings
2. Students learn to research and understand the unique needs of a company around specific challenges
3. Students learn to build empathy for target audiences from different ?cultures?
4. Students learn to develop and test innovative ideas through a rapid iteration cycle
5. Students learn how to create physical prototypes / a visual representation of an idea
6. Students develop the willingness to take a risk and the ability to deal with failure CO2: Professionalism
1. Students develop professional interpersonal and presentation skills
2. Students develop professional communication skills such as interviewing and crafting professional emails
3. Students learn to take ownership of the quality of their work and final products
4. Students understand their duty to maintain ethical standards in product and strategy design
5. Students understand the value of and have tools to develop a strong network CO3: Leadership and teamwork
1. Students develop self awareness of personal leadership style and how to effectively work as a member of a team
2. Students collaborate on a variety of projects
3. Students develop communication skills necessary to facilitate high performance team formation and maintenance (e.g., leveraging the skills and abilities of all team members, valuing cross-disciplinary/cultural contributions, engaging in difficult conversations and resolving conflict) |
Unit-1 |
Teaching Hours:10 |
Module 1: Intro to Design Thinking and Product Design
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Introduction to Design Thinking Introduction to Design Research Strategies Introduction to Synthesis Introduction to Ideation and Prototyping Strategies | |
Unit-2 |
Teaching Hours:10 |
Module 2:Â Team Work and Service Design
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Team work discussion + Launch of Service challenge Design Research - tools for observation + immersion Journey mapping and ideation Develop Final Presentations Final Presentations and Leadership Styles discussion | |
Unit-3 |
Teaching Hours:10 |
Module 3:Â Business or Systems Design
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Launch final challenge – system or student challenge Business Model Canvas and Design Research Visualizing ideas Communicating ideas and effective storytelling Final Presentations and class celebration | |
Text Books And Reference Books: Essential References: 1. Design Your Thinking: The Mindsets, Toolsets and Skill Sets for Creative Problem-solving Hardcover – 23 December 2020, by Pavan Soni. 2. The Design Thinking Toolbox: A Guide to Mastering the Most Popular and Valuable Innovation Methods, by Michael Lewrick, Patrick Link, Larry Leifer. 3. Design Thinking: Understanding How Designers Think and Work, by Nigel Cross, BERG, Oxford, Newyork. | |
Essential Reading / Recommended Reading Recommended References: 1. HBR's 10 Must Reads on Design Thinking (with featured article "Design Thinking" By Tim Brown) Paperback – 10 August 2020, by Publisher : Harvard Business Review Press (10 August 2020); Penguin Random House. 2. Change by Design, Revised and Updated: How Design Thinking Transforms Organizations and Inspires Innovation, by Tim Brown. Publisher HarperCollins, 2019; ISBN 0062856715, 9780062856715. 3. This is Service Design Thinking: Basics, Tools, Cases, by Marc Stickdorn, Jakob Schneider, Publisher BIS Publ., 2012; ISBN 906369279X, 9789063692797 | |
Evaluation Pattern Evaluation Pattern: This courses do not have CIA-1-2-3 and ESE. It has only Overall CIA (out of 100). This will be treated as the final ESE.
The following case studies will be given for the evaluation of overall CIA.
1. Case Studies focused on product design. 2. Case Studies focused on service design. 3. Case Studies focused on systems or business design. | |
CS631P - INTERNET OF THINGS (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course objectives: This course introduces the basic concepts of IoT, the functionalities of different types of sensors, actuators, and microcontrollers. It covers the protocols used in different layers and gives insight on programming IoT for different domains. |
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Course Outcome |
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CO 1: Explain the fundamental building blocks of an IoT environment from a logical and physical perspective. CO 2: Summarize various IoT protocols in Application and Network layers by outlining their advantages and disadvantages. CO 3: Develop programing skills to design IoT solutions using Arduino and Raspberry Pi to solve real life problems CO 4: Experiment with Arduino, CDAC, and Raspberry Pi to choose the appropriate hardware for different IoT projects. CO 5: Survey successful IoT products and solutions to analyze their architecture and technologies. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION AND BACKGROUND
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Definition and Characteristics of IoT, Physical Design of IoT: Things in IoT, Logical Design of IoT: IoT functional Blocks, IoT Communication Blocks, IoT communication APIs, IoT Enabling Technologies: WSN, Cloud Computing, Big Data Analysis, Communication Protocols, Embedded Systems. | |
Unit-2 |
Teaching Hours:9 |
IOT HARDWARE, DEVICES AND PLATFORMS
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Basics of Arduino: The Arduino Hardware, The Arduino IDE, Basic Arduino Programming, Basics of Raspberry pi: Introduction to Raspberry Pi, Programming with Raspberry Pi | |
Unit-3 |
Teaching Hours:9 |
IOT PROTOCOLS
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IoT Architecture: Web of Things versus Internet of Things – Two Pillars of the Web – Unified Multitier WoT Architecture, Cloud Providers and Systems, The Cloud of Things Architecture. IoT Protocols: Application Protocols, Service Discovery Protocols, Infrastructure Protocols, IoT Data Link Protocols, Network Layer Routing Protocols, Network Layer Encapsulation Protocols, Session Layer Protocols. | |
Unit-4 |
Teaching Hours:9 |
IOT PROGRAMMING
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Arduino Programming: Serial Communications, Getting input from sensors, Visual, Physical and Audio Outputs, Remotely Controlling External Devices, Wireless Communication. Programming with Raspberry Pi: Basics of Python Programming, Python packages of IoT, Data communiation to Cloud, and case study | |
Unit-5 |
Teaching Hours:9 |
DOMAIN SPECIFIC IOT
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Home automation, Smart cities, Smart Environment, IoT in Energy, Logistics, Agriculture, Industry and Health & Life style sectors. | |
Text Books And Reference Books: 1. Vijay Madisetti and ArshdeepBahga, “Internet of Things (A Hands-on-Approach)”, 1st Edition, VPT, 2014. 2. Margolis, Michael. “Arduino Cookbook: Recipes to Begin, Expand, and Enhance Your Projects. " O'Reilly Media, Inc.", 2011. 3. Monk, Simon. Raspberry Pi cookbook: Software and hardware problems and solutions. " O'Reilly Media, Inc.", 2016. | |
Essential Reading / Recommended Reading 1. The Internet of Things: Applications to the Smart Grid and Building Automation by – Olivier Hersent, Omar Elloumi and David Boswarthick – Wiley Publications -2012. 2. Vijay Madisetti and Arshdeep Bahga, “Internet of Things (A Hands-on-Approach)”, 1st Edition, VPT, 2014. | |
Evaluation Pattern CIA 70 ESE 30 | |
CS632P - COMPILER DESIGN (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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To have the better understanding of: • Design principles of a Compiler. • Various parsing techniques • Different levels of translation • Optimization and generation of machine codes |
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Course Outcome |
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CO1: Explain the concepts and different phases of compilation with Compiler Construction Tools CO2: Interpret language tokens using regular expressions and design lexical analyzer for a language. CO3: Build top down parsing, bottom up parsing and parse tree representation of the input. CO4: Outline intermediate code for the statements during the process of compilation. CO5: Experiment the optimization techniques to intermediate code and generate machine code for high level language program |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION TO COMPILERS
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Introduction- Structure of a compiler — Lexical Analysis — Role of Lexical Analyzer — The Phases of Compiler- Grouping of the phases – Errors in different phases - Input Buffering — Specification of Tokens — Recognition of Tokens — Lex — Finite Automata — Regular Expressions to Automata — Minimizing DFA. | |
Unit-2 |
Teaching Hours:9 |
SYNTAX ANALYSIS
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Role of Parser — Grammars — Error Handling — Context-free grammars — Writing a grammar — Top Down Parsing —Recursive Descent Parser - Predictive Parser – Bottom Up Parser – SR Parser , LR Parser - SLR – CLR - LALR— Error Handling and Recovery in Syntax Analyzer- Case study : YACC | |
Unit-3 |
Teaching Hours:9 |
INTERMEDIATE CODE GENERATION
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Syntax Directed Definitions, Evaluation Orders for Syntax Directed Definitions, Intermediate Languages: Syntax Tree, Three Address Code, Types and Declarations, Translation of Expressions, Type Checking. | |
Unit-4 |
Teaching Hours:9 |
RUN-TIME ENVIRONMENT AND CODE GENERATION
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Storage Organization, Stack Allocation Space, Access to Non-local Data on the Stack, Heap Management — Issues in Code Generation — Design of a simple Code Generator - Incremental Design: A Case Study of a compiler | |
Unit-5 |
Teaching Hours:9 |
CODE OPTIMIZATION
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Principal Sources of Optimization — Peep-hole optimization — DAGOptimization of Basic Blocks-Global Data Flow Analysis — Efficient Data Flow Algorithm | |
Text Books And Reference Books: T1. Alfred V Aho, Monica S. Lam, Ravi Sethi and Jeffrey D Ullman, “Compilers – Principles, Techniques and Tools”, 2nd Edition, Pearson Education, 2007. | |
Essential Reading / Recommended Reading R1. Randy Allen, Ken Kennedy, “Optimizing Compilers for Modern Architectures: ADependence-based Approach”, Morgan Kaufmann Publishers, 2002. R2. Steven S. Muchnick, “Advanced Compiler Design and Implementation, “MorganKaufmann Publishers - Elsevier Science, India, Indian Reprint 2003. R3. Keith D Cooper and Linda Torczon, “Engineering a Compiler”, Morgan Kaufmann Publishers Elsevier Science, 2004 | |
Evaluation Pattern CIA=70 ESE=30 | |
CS642E01 - MOBILE APPLICATION DEVELOPMENT (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course introduces the basic design and development of Mobile applications and focuses on developing mobile applications for Windows, Android, and IOS. |
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Course Outcome |
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CO 1: Explain the concepts in mobile applications and its development. CO 2: Build an interface for mobile applications and web applications. CO 3: Design mobile application for Android platform using primitive UI features, SQLite and GPS. CO 4: Design a mobile application for the Android platform using advanced features like animations and graphics. CO 5: Develop a mobile application for IOS platform. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
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Introduction to mobile applications – cost of development - Market and business drivers for mobile applications – Publishing and delivery of mobile applications – Requirements gathering and validation for mobile applications. Third party Frameworks. - Mobile Content- Mobile Applications. | |
Unit-2 |
Teaching Hours:9 |
BASIC DESIGN
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Introduction to Web Services– Web service language Format –Web service creation: Case study– Mobile User Interface Design using Hybrid app development Tools. – Environment Setup- Understanding CLI - Layout – Building a simple app- Mobile Web Apps Using HTML5. Designing applications with multimedia and web access capabilities - Storing data in Firebase. | |
Unit-3 |
Teaching Hours:9 |
TECHNOLOGY II ANDROID 1
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Introduction – Establishing the development environment – Android architecture – Activities and views – Interacting with UI – Persisting data using SQLite – Packaging and deployment – Interaction with server side applications – Using Google Maps, GPS and Wifi – Integration with social media applications. | |
Unit-4 |
Teaching Hours:9 |
TECHNOLOGY II ANDROID 2
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Animating views - Scenes and Transitions, Frame Animations, Tween Animation, scale, rotate, translate, alpha, Interpolation, Canvas/Drawing into a view, Surface View/Surface Holder, Adding animations - Crossfading two views. Graphics: Graphics & Multimedia – Introduction to Graphics, displaying bitmaps, displaying graphics with OpenGL ES, defining and drawing shapes | |
Unit-5 |
Teaching Hours:9 |
TECHNOLOGY III - IOS
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Introduction to Objective C – iOS features – UI implementation – Touch frameworks – Data persistence using Core Data and SQLite – Location aware applications using Core Location and Map Kit – Integrating calendar and address book with social media application – Using Wifi – CASE STUDY- iPhone marketplace and mobile application development. | |
Text Books And Reference Books:
| |
Essential Reading / Recommended Reading
| |
Evaluation Pattern CIA: 50 ESE: 50 | |
CS642E03 - ADVANCED DATABASES (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Provides insight on the needs of different databases, data models, get familiarized with transaction management and intelligent of the database. |
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Course Outcome |
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CO 1: Interpret ER models for relational database design. CO 2: Experiment with Object Databases and XML for advanced databases. CO 3: Identify query optimization parameters and appropriate scheduling for improved transactions. CO 4: Compare the working principles of concurrency and recovery methods for a database. CO 5: Examine solutions to problems pertaining to security aspects for a database. |
Unit-1 |
Teaching Hours:9 |
DATABASE MANAGEMENT
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Relational Data Model – SQL - Database Design - Entity-Relationship Model – Relational Normalization – EER - Relational Database Design Using ER-to-Relational Mapping - Mapping EER Model Constructs to Relations. | |
Unit-2 |
Teaching Hours:9 |
ADVANCED DATABASES
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Object Databases – Object database Extensions to SQL-ODMG and ODL –Object Database Conceptual Design- Distributed Transactions- Concurrency control in the Distributed Databases- Replication- Extended Concurrency Control Protocols | |
Unit-3 |
Teaching Hours:9 |
QUERY AND TRANSACTION PROCESSING
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Query Processing Basics – Heuristic Optimization –Selectivity, Cost, Size Estimation – Transaction and System Concepts-Properties of Transactions – Architecture – Characterizing Schedules Based on Recoverability – Characterizing Schedules Based on Serializability –Transaction Support in SQL | |
Unit-4 |
Teaching Hours:9 |
CONCURRENCY CONTROL AND RECOVERY
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Block Chain Databases- Block Chain Properties- Achieving Blockchain Properties via Cryptographic Hash Functions- Consensus- data management in Block chain- Smart Contracts- Performance Enhancement- Emerging Applications | |
Unit-5 |
Teaching Hours:9 |
DATABASE SECURITY
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Introduction to Database Security Issues- Discretionary Access Control Based on Granting and Revoking Privileges- Mandatory Access Control and Role-Based Access Control for Multilevel Security - SQL Injection- Statistical Database Security- Flow Control- Encryption and Public Key Infrastructures- Privacy Issues and Preservation- Challenges of Database Security- Oracle Label-Based Security | |
Text Books And Reference Books: 1. Abraham Silberschatz, Henry. F. Korth, S.Sudharsan, “Database System Concepts”, 7th Edition., Tata McGraw Hill, 2019. 2. R. Elmasri and S.B. Navathe, “Fundamentals of Database Systems”, 7th Edition, Pearson Edition, 2021. 3. R. Elmasri and S.B. Navathe, “Fundamentals of Database Systems”, 6th Edition, Addison Wesley, 2010 | |
Essential Reading / Recommended Reading 1. Raghu Ramakrishnan & Johannes Gehrke, “Database Management Systems”, 3rd Edition, TMH, 2003. 2. 2. Philip M. Lewis, Arthur Bernstein, Michael Kifer, “Databases and Transactio Processing: An Application-Oriented Approach”, Addison-Wesley, 2002 | |
Evaluation Pattern CIA Marks- 50% ESE Marks- 50% | |
CS642E06 - SYSTEM SOFTWARE (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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● To understand the relationship between system software and machine architecture. ● To know the design and implementation of assemblers. ● To know the design and implementation of linkers and loaders. ● To have an understanding of macro processors. To have an understanding of system software tools. |
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Course Outcome |
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CO 1 : Summarize the basic concepts of SIC and SIC/XE architecture CO 2: Make Use of the concept of assembler according to SIC and SIC/XE architecture with real world cases CO 3: Utilize the detailed working of linker and loader with respect to SIC and SIC/XE architecture for real world cases CO 4: Make use of Microprocessor functionalities according to SIC and SIC/XE architecture with real world cases CO 5 : Examine the role of compiler in programming environment |
Unit-1 |
Teaching Hours:9 |
MACHINE STRUCTURE AND EVOLUTION OF A PROGRAMMING SYSTEM
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Introduction to System Software, Components of System Software, Evolution of System Software, Assembler, Loader, Macros, Compilers, Simplified Instructional Computer: SIC machine architecture, SIC/XE machine architecture, SIC programming examples. | |
Unit-2 |
Teaching Hours:9 |
ASSEMBLER
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Basic assembler functions (SIC assembler, algorithm and data structure), Machine dependent assembler features (Instruction formats and addressing modes, program relocation), Machine independent assembly features (Literals, Symbol defining statements, expressions, program blocks, control sections and program linking), Assembler design options (One pass assembler, multi pass assembler). | |
Unit-3 |
Teaching Hours:9 |
LOADERS AND LINKERS
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Basic loader functions (Design of an absolute loader, simple bootstrap loader), Machine dependent loader features (Relocation, program linking, algorithm and data structures for a linking loader), Machine independent loader features (Automatic library search, loader options), Loader design options (Linkage editor, dynamic linking, bootstrap loaders). | |
Unit-4 |
Teaching Hours:9 |
MACRO PROCESSOR
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Macro Instructions, Features of a macro facility (Macro instruction arguments, Conditional macro expansion, Macro calls within macro, Macro instructions defining macros), Implementation (Two pass algorithm, Single pass algorithm | |
Unit-5 |
Teaching Hours:9 |
COMPILERS
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Part1: Basic elements, Syntactic units and interpreting meaning, Intermediate form (Arithmetic statements, non-arithmetic statements, non-executable statements), Storage allocation, Code generation, Optimization (Machine independent, Machine dependent, Assembly phase). Part2: Phases of the compiler (Lexical phase, Syntax phase, Interpretation phase, Optimization, Storage assignment, Code generation, Assembly phase), Passes of a compiler. Case study | |
Text Books And Reference Books: 1. Donovan, “John, System programming”, Tata McGraw-Hill, Reprint 2008. 2. Beck, Leland, “System Software: An Introduction to System Programming”, Addison-Wesley, 3rd Edition, Reprint 2009 | |
Essential Reading / Recommended Reading 1. Dhamdhere D M, “Systems programming and operating systems”, Tata McGraw-Hill, Reprint 2011 | |
Evaluation Pattern CIA- 50% out of 100 ESE-50% out of 100 | |
CS681 - SERVICE LEARNING (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Objective of this course is to Promotes the problem solving skills by apply the engineering knowledge for the societal problems. Problems willl be based on Sustainable Global Development Goals (SDG) |
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Course Outcome |
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CO1: Apply the concepts of Computer Science and Information Technology to solve given real world societal problems through prototypes. CO2: Design solutions to given real world societal problems through working prototypes CO3: Select appropriate hardware and software as per the requirement of the project designed to solve given real world societal problems. CO4: Understand the impact of the developed projects on environmental factors. CO5: Demonstrate project management skills including handling the finances in doing projects for given real world societal problems. |
Unit-1 |
Teaching Hours:30 |
Proto Type Development
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Students are expected to asscoiate with an NGO or a community to solve the societal problems focusing on Sustainable development Goals (SDG)
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Text Books And Reference Books: NA | |
Essential Reading / Recommended Reading NA | |
Evaluation Pattern The evaluation comprises of following components: 1. Identification of problem in the community Inline with SDG topics ( 5marks) 2. Literature Survey (5 marks) 3. Proof of concept ( 5 Marks) 4. Ideathon/Poster Presentation/Paper presentation (10 marks) 5. Prototype evaluation (5 marks) 6. Deployment (10 marks) 7. Community Engagement (5 marks) 8. ESE Project Presentation (5 marks)
Total Marks : 50 Marks
| |
CSHO681AIP - AI PROJECT /CERTIFICATE COURSES (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Description Through this capstone project students will get an opportunity to apply the knowledge and skills in artificial intelligence that they have gained.
Course Objectives To learn about real-world problems and to get their solutions using artificial intelligence. To develop team working skills and perform with the team. To provide the opportunity to carry out certification courses on artificial intelligence. |
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Course Outcome |
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CO1: Design engineering solutions to complex real world problems using research literature for societal applications through independent study. CO2: Use appropriate hardware and software depending on the nature of the project with an understanding of their limitations. CO3: Demonstrate teamwork and leadership skills with professional ethics and prepare a project report in the prescribed format. CO4: Understand the impact of the developed projects on environmental factors. CO5: Demonstrate project management skills including handling the finances in doing projects for given real world societal problems. |
Unit-1 |
Teaching Hours:15 |
UNIT 1
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Design engineering solutions to complex real world problems using research literature for societal applications through independent study. | |
Unit-2 |
Teaching Hours:15 |
UNIT 2
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Use appropriate hardware and software depending on the nature of the project with an understanding of their limitations. | |
Unit-3 |
Teaching Hours:15 |
Unit 3
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Demonstrate teamwork and leadership skills with professional ethics and prepare a project report in the prescribed format. | |
Unit-4 |
Teaching Hours:15 |
Unit 4
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Understand the impact of the developed projects on environmental factors | |
Unit-5 |
Teaching Hours:15 |
Unit 5
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Demonstrate project management skills including handling the finances in doing projects for given real world societal problems | |
Text Books And Reference Books: Based on the project the reference materials will be suggested. | |
Essential Reading / Recommended Reading · Based on the project the additional reference materials will be suggested. | |
Evaluation Pattern · Continuous Internal Assessment: 50 Marks · End Semester Examination: 50 Marks | |
CSHO681CSP - CS PROJECT/CERTIFICATE COURSES (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Description Through this capstone project students will get an opportunity to apply the knowledge and skills in cyber security that they have gained.
Course Objectives To perform a task involving cyber security research or design, that is carefully planned to achieve a particular aim. To learn modular programming - analyse problems, design solutions. To learn new tools and implement the system as a team/individual. |
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Course Outcome |
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CO1: Design engineering solutions to complex real world problems using research literature for societal applications through independent study. CO2: Use appropriate hardware and software depending on the nature of the project with an understanding of their limitations. CO3: Demonstrate teamwork and leadership skills with professional ethics and prepare a project report in the prescribed format. CO4: Understand the impact of the developed projects on environmental factors. CO5: Demonstrate project management skills including handling the finances in doing projects for given real world societal problem. Handling the finances in doing projects for given real world societal problems. |
Unit-1 |
Teaching Hours:15 |
Unit 1
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Design engineering solutions to complex real world problems using research literature for societal applications through independent study. | |
Unit-2 |
Teaching Hours:15 |
Unit 2
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Use appropriate hardware and software depending on the nature of the project with an understanding of their limitations. | |
Unit-3 |
Teaching Hours:15 |
Unit 3
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Demonstrate teamwork and leadership skills with professional ethics and prepare a project report in the prescribed format. | |
Unit-4 |
Teaching Hours:15 |
Unit 4
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Understand the impact of the developed projects on environmental factors | |
Unit-5 |
Teaching Hours:15 |
Unit 5
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Demonstrate project management skills including handling the finances in doing projects for given real world societal problem. Handling the finances in doing projects for given real world societal problems | |
Text Books And Reference Books: Based on the project the reference materials will be suggested.
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Essential Reading / Recommended Reading Based on the project the additional reference materials will be suggested.
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Evaluation Pattern Continuous Internal Assessment: 50 marks End Semester Examination: 50 marks | |
CSHO681DAP - DA PROJECT/CERTIFICATE COURSES (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Description Through this capstone project students will get an opportunity to apply the knowledge and skills in data analytics that they have gained.
Course Objectives To test the skills in data analysis, data visualization, data wrangling, regression, machine learning etc. To learn modular programming - analyse problems, design solutions, learn new tools and implement the system as a team/ individual.
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Course Outcome |
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CO1: Design engineering solutions to complex real world problems using research literature for societal applications through independent study. CO2: Use appropriate hardware and software depending on the nature of the project with an understanding of their limitations. CO3: Demonstrate teamwork and leadership skills with professional ethics and prepare a project report in the prescribed format. CO4: Understand the impact of the developed projects on environmental factors. CO5: Demonstrate project management skills including handling the finances in doing projects for given real world societal problem. Handling the finances in doing projects for given real world societal problems . |
Unit-1 |
Teaching Hours:15 |
Unit 1
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Design engineering solutions to complex real world problems using research literature for societal applications through independent study. | |
Unit-2 |
Teaching Hours:15 |
Unit 2
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Use appropriate hardware and software depending on the nature of the project with an understanding of their limitations. | |
Unit-3 |
Teaching Hours:15 |
Unit 3
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Demonstrate teamwork and leadership skills with professional ethics and prepare a project report in the prescribed format. | |
Unit-4 |
Teaching Hours:15 |
Unit 4
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Understand the impact of the developed projects on environmental factors. | |
Unit-5 |
Teaching Hours:15 |
Unit 5
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Demonstrate project management skills including handling the finances in doing projects for given real world societal problem. Handling the finances in doing projects for given real world societal problems
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Text Books And Reference Books: Based on the project the reference materials will be suggested.
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Essential Reading / Recommended Reading Based on the project the additional reference materials will be suggested.
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Evaluation Pattern Continuous Internal Assessment: 50 marks End Semester Examination: 50 marks | |
IT633P - DATA WAREHOUSING AND DATA MINING (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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To introduce the necessary background of data warehouse, the basic data mining algorithms and its applications. Syllabus focuses on data warehousing architecture, Multidimensional Data Model, Pre-processing, Association rule mining, Classification, Prediction , Clustering and Recent trends in higher order database systems |
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Course Outcome |
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CO1: Identify the differences between relational database and data warehouses, the need for data warehousing to formulate the decision support system an engineering specialization for the prediction and modelling to complex engineering activities. CO2: Summarize the dominant data warehousing architectures and analyse their implementation details to develop multidimensional data models to analyse complex engineering problems. CO3: Implement various data pre-processing techniques to design data warehouses that meet the specified needs of the society with appropriate environmental considerations. CO4: Analyse the various clustering and classification algorithm functionalities and evaluate their merits and demerits to acquire research based knowledge for the synthesis of the information to provide valid conclusion. CO5: Explain advanced data mining concepts and outline their scope of providing IT solutions for different domains which helps in the betterment of life. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION AND DATA WAREHOUSING
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Introduction, Data Warehouse, Multidimensional Data Model, Data Warehouse Architecture, Implementation, Further Development, Data Warehousing to Data Mining | |
Unit-2 |
Teaching Hours:9 |
DATA PREPROCESSING, LANGUAGE, ARCHITECTURES, CONCEPT DESCRIPTION
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Why Preprocessing, Cleaning, Integration, Transformation, Reduction, Discretization, Concept Hierarchy Generation, Data Mining Primitives, Query Language, Graphical User Interfaces, Architectures, Concept Description, Data Generalization, Characterizations, Class Comparisons, Descriptive Statistical Measures.
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Unit-3 |
Teaching Hours:9 |
ASSOCIATION RULES
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Association Rule Mining, Single-Dimensional Boolean Association Rules from Transactional Databases, Multi-Level Association Rules from Transaction Databases | |
Unit-4 |
Teaching Hours:9 |
CLASSIFICATION AND CLUSTERING
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Classification and Prediction, Issues, Decision Tree Induction, Bayesian Classification, Association Rule Based, Other Classification Methods, Prediction, Classifier Accuracy, Cluster Analysis, Types of data, Categorization of methods, Partitioning methods, Outlier Analysis. | |
Unit-5 |
Teaching Hours:9 |
RECENT TRENDS
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Multidimensional Analysis and Descriptive Mining of Complex Data Objects, Spatial Databases, Multimedia Databases, Time Series and Sequence Data, Text Databases, World Wide Web, Applications and Trends in Data Mining | |
Text Books And Reference Books: T1. J. Han, M. Kamber, “Data Mining: Concepts and Techniques”, Harcourt India / Morgan Kauffman, 2011. T2. Pang-Ning Tan, Michael Steinbach, Vipin Kumar: Introduction to Data Mining, Pearson Education, 2012.
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Essential Reading / Recommended Reading R1.K.P.Soman, ShyamDiwakar, V.Ajay: Insight into Data Mining – Theory and Practice, PHI, 2012 R2. David Hand, Heikki Manila, PadhraicSymth, “Principles of Data Mining”, PHI 2012. R3. W.H.Inmon, “Building the Data Warehouse”, 3rd Edition, Wiley, 2011. R4. Alex Bezon, Stephen J.Smith, “Data Warehousing, Data Mining & OLAP”, MeGraw-Hill Edition, 2001
R5. PaulrajPonniah, “Data Warehousing Fundamentals”, Wiley-Interscience Publication, 2003 | |
Evaluation Pattern
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IT642E02 - FOUNDATIONS TO BLOCKCHAIN TECHNOLOGY (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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To introduce students to blockchain technology along with its different properties and applications. |
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Course Outcome |
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CO1: .Explain emerging abstract models for Blockchain Technology. CO2: Identify major research challenges and technical gaps existing between theory and practice in crypto currency domain. CO3: Demonstrate conceptual understanding of the function of Blockchain as a method of securing distributed ledgers, how consensus on their contents is achieved, and the new applications that they enable. CO4: Analyze hyperledger Fabric and Etherum platform to implement the Block chain Application. CO5: Role of blockchain in different areas including industrial applications. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION TO BLOCKCHAIN
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Blockchain- A history of Blockchain-how the computation environment evolved, What is a Blockchain,Problems with centralized system, Centralized vs decentralized vs distributed, Blockchain as Public Ledgers,Bitcoin and Blockchain, Technology behind bitcoin—The Blockchain, Blockchain 2.0 and Smart Contracts,Block in a Blockchain- securing data, Structure of a Block, Block Header, The blockchain Replicas, DistributedConsensus, Permission less consensus and Permissioned Model of Blockchain 2.0, Cryptographically securedHash Function, Cryptographically secured chain of blocks, Properties of a hash function-Hash pointer, Merkle tree and its use. | |
Unit-2 |
Teaching Hours:9 |
BITCOIN AND CRYPTOCURRENCY
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A basic crypto primitives: Digital signature, reducing signature size, introduction to cryptocurrency usingdigital signature and hashchain, What is bitcoin, Creation of bitcoins, Payments and double spending, FORTH– How FORTH works, Bitcoin Scripts , Bitcoin P2P Network, Transaction in Bitcoin Network , Block Mining inbitcoin network, Block Flooding, Block propagation and block relay | |
Unit-3 |
Teaching Hours:9 |
BITCOIN CONSENSUS
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Introduction to Consensus, Distributed consensus, Consensus in a Bitcoin network, Proof of Work (PoW)-Cryptographic Hash as PoW, Hashcash PoW, Bitcoin PoW, Tempering of PoW- Sybil attacks, DoS attacks,PoW power consumption, monopoly problem- Proof of Stake, Proof of Burn, Proof of Elapsed Time. Basics ofPoET, Mining bitcoin, Difficulty in mining, Hash rate vs difficulty, Mining Pool, Permissioned model ofblockchain and use cases, Design issues for Permissioned Blockchains, State machine replication, smartcontract state machine – crowd funding, Distributed state machine replication | |
Unit-4 |
Teaching Hours:9 |
DISTRIBUTED CONSENSUS, HYPER LEDGER FABRIC & ETHERUM
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Consensus algorithm- RAFT Consensus, PAXOS consensus, Byzantine general model, Byzantine generalproblem, Lamport-Shostak-Pease, Practical Byzantine Fault Tolerance. Introduction to hyperledger fabric v1.1,Architecture of Hyperledger fabric v1.1, Ethereum: Ethereum network, EVM, Transaction fee, Mist Browser,Ether, Gas, Solidity, Smart contracts, Truffle-Design and issue Crypto currency, Mining, DApps, DAO. | |
Unit-5 |
Teaching Hours:9 |
BLOCKCHAIN APPLICATIONS
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Understanding business problems, understanding the participants, Building communities in blockchain network, Blockchain in Financial services, Supply chain management, revolutionizing global trade. | |
Text Books And Reference Books: T1. Bashir, Imran, “Mastering Blockchain: Deeper insights into decentralization, cryptography, Bitcoin, and popular Blockchain frameworks”, 2017. T2. Bikramaditya Singhal, Gautam Dhameja, Priyansu Sekhar Panda, “Beginning Blockchain: A Beginner's Guide to Building Blockchain Solutions”, Apress.
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Essential Reading / Recommended Reading R1. Tailor Jacobs, "Blockchain: A Step-by-step Guide for Beginners to Implementing Blockchain Technology and Leveraging Blockchain Programming", Tailor Jacobs, 2017. R2. David A Shrier, "Basic Blockchain: What It Is and How It Will Transform the Way We Work and Live", Robinson Publication. R3. Stephen P Williams, "Blockchain: The next Every Thing, Stephen P Williams", 2019.
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Evaluation Pattern CIA - 50% out of 100 ESE - 50% out of 100
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MIIMBA634 - DATA ANALYSIS FOR MANAGERS (2021 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Objectives: This course attempts to enable the students to conceptualize business problems in statistical terms and to enhance their understanding and application of fact and evidence-based decision-making process. |
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Course Outcome |
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CO1: Identify suitable data visualization technique for the given data set. CO2: Apply an appropriate probability distribution technique for the given set of data. CO3: Design sampling frame based on the context of decision-making. CO4: Analyse statistical data to support fact-based decision making. CO5: Develop models to understand the relationship between variables. |
Unit-1 |
Teaching Hours:12 |
Data Visualization
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Frequency distributions, histograms, stem-and-leaf displays, bar charts, pie charts, and scatter plots. Data Preparation: Editing, coding, data entry, cross-tabulation, and graphical displays using MS Excel 12. | |
Unit-2 |
Teaching Hours:12 |
Introduction to Probability and Probability Distributions
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Probability - Event algebra*. Conditions of statistical dependence and independence, Types of probability, probabilities under conditions of statistical independence, conditional probability under statistical dependence, Bayes’ theorem and its applications. Probability Distributions - Meaning of Probability Distribution, Random variables, Discrete and continuous random variables. Expected value, Use of expected value in decision making, Variance of a random variable. Binomial, Poisson, Uniform, Normal and Exponential distributions and their properties and applications. | |
Unit-3 |
Teaching Hours:12 |
Sampling Methods Estimation and Testing Statistical Hypothesis
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Sampling - Need, benefits and limitations. Probability and Non-probability sampling methods. Sampling distributions, Central Limit Theorem. Estimation - Point and Interval estimators of mean and proportion - Determining sample size using confidence interval approach. Testing Hypothesis - Concepts basic to hypothesis, null and alternative hypothesis, testing procedure, level of significance, Types of errors. Measuring power of a hypothesis test. Testing of means and proportions for small and large samples, testing of difference between means and proportions for small and large samples. | |
Unit-4 |
Teaching Hours:12 |
Chi-square Test and Analysis of Variance
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Chi-Square test of goodness of fit and test of independence. ANOVA, Multiple comparison procedures. Inference about population variance. Overview of Analysis of CRD, RBD, LSD, and factorial designs. t-Test, Chi-square test for Goodness of Fit and independence of attributes, ANOVA using MS Excel | |
Unit-5 |
Teaching Hours:12 |
Correlation and Regression
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Concept of Correlation - Measure of Correlation & Interpretation. Simple Linear Regression - Form, fitting, prediction, hypothesis testing in linear regression. Residual analysis for validation of assumptions* - normality, homoscedasticity, outliers and influential observations. Correlation and Regression using MS Excel. | |
Text Books And Reference Books: Anderson, D.R., Sweeny, D.J., Williams, T.A., Camm, J.D., Cochran, J.J. (2017). Statistics for business & economics, 13thEdition. Boston: Cengage Learning. | |
Essential Reading / Recommended Reading
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Evaluation Pattern CIA1 - Assignment based on Unit 1 of 20 marks CIA2 - Midterm exam based on Unit 2 and 3 of 50 marks CIA3 - Assignment based on Unit 4 and 5 of 20 marks. | |
CEOE731 - SUSTAINABLE AND GREEN TECHNOLOGY (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course teaches the students, the Engineering and Design processes in alternative and renewable energy systems. |
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Course Outcome |
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CO1: Demonstrate the use of the concepts underlying the use sustainability CO2: Calculate energy balance with a focus on batteries and fuel cells. CO3: Synthesize the concepts of green transport systems.
CO4: Describe the concepts used to discuss various sustainability concepts such as VSM. CO5: Perform the Life Cycle Analysis calculation (LCA) utilized in sustainability. |
Unit-1 |
Teaching Hours:9 |
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Introduction
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Introduction to definitions and concepts underlying sustainability, State of the world using measures of sustainability | |||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Conservation and Energy Balance
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Mass conservation and closed energy cycles, Green Design and Green Manufacturing Concepts. Energy Balance – The case of electric batteries and fuel cells | |||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Transport Systems
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Mass and Energy Transport Systems, Economic Concepts: Net Present Value (NPV) calculations | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Optimization
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Optimization Problems and resource allocation in sustainability, Value Stream Mapping (VSM) – Theory and practice | |||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Life Cycle Analysis
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Life Cycle Analysis (LCA): Theory – Applications – Examples | |||||||||||||||||||||||||||||||
Text Books And Reference Books: T1. Dresner, Simon. (2008) The Principles of Sustainability 2nd edition. Styluspub Publishing Inc., Sterling, Virgina. T2. Epstein, Marc (2008) Making Sustainability Work. Berrett-Koehler, Publishers, San Francisco, California. | |||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading R1. AME, Association for Manufacturing Excellence (2007) Green Manufacturing: Case Studies in Lean Manufacturing and Sustainability. Productivity Press, Inc. R2. Doppelt, Robert. (2010) The Power of Sustainability Thinking. Stylus Publishers, Sterling, Virginia. R3. Dornfeld, David (2010) Green Manufacturing: Fundamentals and Applications. Springer. Berlin, Germany. R4. Epstein, Matt and John Elkington (2008) Making Sustainability Work: Best Practices in Managing and Measuring Corporate Social, Environmental, and Economic Impacts. Berrett_Koehler Publishers, San Francisco, California. R5. Hansen, J. (2009) Storms of My Grandchildren: The Truth About the Coming Climate Catastrophe and Our Last Chance to Save Humanity. Bloomsbury Press. R6. Hardisty, P.E. (2010) Environmental and Economic Sustainability. CRC Press. R7.Hitchcock, Darcy and Marsha Willard. (2008) The Step-By-Step Guide to Sustainability Planning. Stylus Publishing, Sterling, Virginia. R8. ISO 14040 “Environment Management – Life Cycle Assessment – Principles and Framework” Geneva, Switzerland (2007) R9. Krosinsky, Cary and Nick Robing (2008) Sustainability Investing. Stylus Publishing, Sterling, Virginia. R10.LEED: “Building Ratings System for New Construction and Major Renovations” Version 3.1: U.S. Green Building Council 2009. R11.Matthew, R.A. (2010) Global Environmental Change and Human Security. MIT Press. R12. McKenny, M., Schock, R. and Yonavjak, L. (2007) Environmental Science: Systems Solutions 4th edition Jones and Bartlett Publishers.
R13. Pierce, J. and G. Randeis (2010) Contemporary Bioethics: A Reader with Cases. Oxford University Press. | |||||||||||||||||||||||||||||||
Evaluation Pattern
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CEOE732 - AIR POLLUTION AND CONTROL (2020 Batch) | |||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:03 |
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Course Objectives/Course Description |
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Objective of this is to know the sources, characteristics and effects of air and noise pollution and the methods of controlling the same. The student is expected to know about source inventory and control mechanism like.
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Course Outcome |
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CO1: Identify the major sources and sinks of air pollutants. CO2: Understand the key chemical transformations of air pollution. CO3: Relate air pollution regulation and its scientific basis. CO4: Describe engineering solutions to air pollution problems. CO5: Study the burning environmental issues |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION
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Definition – Classification and Characterization of Air Pollutants, Emission Sources, Behavior and Fate of air Pollutants, Chemical Reactions in the Atmosphere, Photo-chemical Smog, Coal-induced smog, Air Pollution Inventories. | |||||||||||||||||||||||||||||||
Unit-1 |
Teaching Hours:9 |
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EFFECTS OF AIR POLLUTION
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On Human Health, Animals, Plants and Materials – Major Environmental Air Pollution Episodes – London Smog, Los Angeles Smog & Bhopal Gas Tragedy. | |||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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METEOROLOGY
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Introduction – Meteorological Variables, Primary and Secondary Lapse Rate, Inversions, Stability Conditions, Windrose, General Characteristics of Stack Plumes, Meterological Models. Industrial Plant Location and Planning | |||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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SAMPLING, ANALYSIS AND CONTROL
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Sampling and Measurement of Gaseous and Particulate matter, Stack Sampling, Analysis of Air Pollutants, Smoke and Smoke Measurement, Air Pollution Control Methods– Particulate, Emission Control, Gravitational Settling Chambers, Cyclone Separators, Fabric Filters, Electrostatic Precipitators, Wet Scrubbers, Selection of a Particulate Collecting Equipment, Control of Gaseous Emissions, Adsorption by Liquids, Adsorption by Solids, Combustion Odours and their control. | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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AIR POLLUTION DUE TO AUTOMOBILES
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Air Pollution due to Gasoline Driven and Diesel Driven Engines, Effects, Direct and Indirect Methods of control | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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STANDARDS AND LEGISLATION
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Air Quality and Emission Standards– Legislation and Regulation, Air Pollution Index. | |||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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BURNING ENVIRONMENTAL ISSUES:
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1.Acid Rain 2.Global Warming 3.Ozone Depletion in Stratosphere 4.Indoor Air Pollution | |||||||||||||||||||||||||||||||
Text Books And Reference Books: T1“Air Pollution – Sampling and Analysis – APHA” T2. “Environmental Engineering and Management” Dhamija S K and kataria S K andSons, Delhi T3. De AK, “Engineers Chemistry”, New Age Publication, Delhi T4. Deswal and SS Deswal; “Environmental Engineering”, Dhanpat Rai andCompany (P) Ltd., Delhi | |||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading R1Harper and Row “Air Pollution –Its origin and control”, Wark. K.and Warner. F. publishers, New York R2. Henry C. Perkins “Air Pollution”, McGraw Hill Ltd. R3. Kendeigh SC, “Ecology”, Prentice Hall of India, Delhi R4. Odum EP, “Fundamentals of Ecology”, Amarind publication Co., Delhi | |||||||||||||||||||||||||||||||
Evaluation Pattern
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CEOE733 - GIS AND REMOTE SENSING TECHNIQUES AND APPLICATIONS (2020 Batch) | |||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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The objective of this course is to provide knowledge and importance of different geospatial tchniques, tools and applications. |
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Course Outcome |
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CO1: Apply the Photogrammetric concepts to determine the ground coordinates CO2: Analyze the remote sensing images visually using Spectral Reflectance characteristics CO3: Create thematic map using GIS Concepts CO4: Establish Relationship between Geographic coordinates and time. |
Unit-1 |
Teaching Hours:6 |
PHOTOGRAMMETRY
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PHOTO GRAMMETRY: Introduction – Basic Principles – Photo theodolite – Definitions – Horizontal and Vertical angle from teerestial photograph – Horizontal position of a point from photo graphic measurement from camera horizontal axis – Elevation of point by photographic measurement – focal length. AERIAL CAMERA – SCALE OF PHOTOGRAPH: Determination of height of lens for a vertical photograph – Relief displacement – Scale of tilted photograph – computation of a length o line between points of different elevation from measurement on a tilted photograph. | |
Unit-2 |
Teaching Hours:6 |
APPLICATION OF PHOTOGRAMMETRY
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DETERMINATION OF FLYING HEIGHT FOR A TILTED PHOTOGRAPH: Tile distortion – Relief displacement – Combined effect of tile and relief – flight planning for Aerial Photogrammetry, Ground control– Stereoscopic vision – Drift mosaics, Relevant numerical examples in the above topics. | |
Unit-3 |
Teaching Hours:12 |
REMOTE SENSING
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REMOTE SENSING: Introduction – Historical sketch of Remote Sensing – Idealized remote sensing – Basic principles of remote sensing – Electromagnetic energy Electromagnetic spectrum- Wave length regions and their application in remote sensing – characteristics of solar radiation – Basic radiation law – EM radiation and atmosphere – Interaction of EM radiation with earth surface – Remote sensing observation platforms – sensors –Application of Remote Sensing. | |
Unit-4 |
Teaching Hours:12 |
GEOGRAPHICAL INFORMATION SYSTEM
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GEOGRAPHICAL INFORMATION SYSTEM, DEFINITION: The four M’s concept – contributing disciplines for GIS, GIS objectives – components of a GIS – Topology – Data models – Data structures – Data base management – Errors in GIS – GIS software packages – Linkage of GIS to remote sensing – Application areas of GIS and Remote sensing. | |
Unit-5 |
Teaching Hours:9 |
Global Navigation and Positioning Systems
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Global Navigation and Positioning Systems Systems: Introduction to Field Astronomy, Introduction to various navigation systems: , GLONASS, Galileo, BeiDou, IRNSS (Indian Region Indian Regional Navigation Satellite System) NAVIC and QZSS. Working Principle of navigation system: Resection and Trilateration Segments of Navigation system: Space Segment, Control Segment and User segment, Ranging and Communication, Surveying and Navigation. | |
Text Books And Reference Books: P.R Wolf and B.A. Dewitt Elementary Photogrammetry, 4th edition, TMH publishing, 2014 (UNIT-1) Lillesand, T., Kiefer, R. W., & Chipman, J. (2015). Remote sensing and image interpretation. John Wiley & Sons. (UNIT-3) Burrough, P. A., McDonnell, R. A., & Lloyd, C. D. (2015). Principles of geographical information systems. Oxford university press (UNIT4) Punmia, B. C., Jain, A. K., & Jain, A. K. (2005). Higher surveying. Laxmi Publ, (3). (UNIT-5) | |
Essential Reading / Recommended Reading R1. Gupta, R. P. (2017). Remote sensing geology. Springer. R2. Kumar, S. (2005). Basics of remote sensing and GIS. Firewall Media. (UNIT 4) R3. Jensen, J. R. (1996). Introductory digital image processing: a remote sensing perspective (No. Ed. 2). Prentice-Hall Inc.. Online Resources: W1. http://www.gisresources.com/ W2. https://onlinecourses.nptel.ac.in/noc17_ce09 | |
Evaluation Pattern CIA-1 : CLASS PERFORMANCE, QUIZ TEST, CLASS TEST (10 MARKS) CIA-2: CENTRALLY CONDUCTED CLOSED BOOK TEST (25 MARKS) CIA-3 : QUIZ TEST, CLASS TEST AND PROJECT BASED LEARNING (10 MARKS) Note: based on the relative performance in the class, continuous assignments are give for better understanding of the concepts. | |
CS743E02 - TCP/IP DESIGN AND IMPLEMENTATION (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
The basic functionalities of TCP/IP Protocols, internals, and implementation of TCP/IP Protocols are elaborated. Understanding the interaction among protocols in the protocol stack and timer management has been discussed. |
|
Course Outcome |
|
CO1: . |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
|
|
Internetworking concepts and architectural model- classful Internet address – CIDR Subnetting and Supernetting –ARP- RARP- IP – IP Routing –ICMP – Ipv6 | |
Unit-2 |
Teaching Hours:9 |
TCP
|
|
Services – header – connection establishment and termination- interactive data flow-bulk data flow- timeout and retransmission – persist timer - keepalive timer- futures and performance | |
Unit-3 |
Teaching Hours:9 |
IP IMPLEMENTATION
|
|
IP global software organization – routing table- routing algorithms-fragmentation and reassembly- error processing (ICMP) –Multicast Processing (IGMP) | |
Unit-4 |
Teaching Hours:9 |
TCP IMPLEMENTATION I
|
|
Data structure and input processing – transmission control blocks- segment format comparison-finite state machine implementation-Output processing- mutual exclusion-computing the TCP data length | |
Unit-5 |
Teaching Hours:9 |
TCP Implementation II
|
|
Timers-events and messages- timer process- deleting and inserting timer event- flow control and adaptive retransmission-congestion avoidance and control – urgent data processing and push function-Case Study Illustrate the silly window syndrome avoidance and trace the TCP transfer | |
Text Books And Reference Books: T1.Douglas E.Comer – “Internetworking with TCP/IP Principles, Protocols and Architecture”, Vol. 1 &2, Sixth Edition, PHI 2014. (Unit I in Comer Vol. 1, Units II, IV & V – Comer Vol. 2 ) T2. W.Richard Stevens, “TCP/IP illustrated”, Volume 1 Pearson Education, 2012 (Unit II) T3. Douglas E. Comer, “Internetworking with TCP/IP”, Volume One (6th Edition) Hardcover May 5, 2014 T4. Fall, Kevin R.; Stevens, W. Richard; Wright, Gary R– “TCP/IP Illustrated, Volume 1 ,Second Edition, PHI 2012 | |
Essential Reading / Recommended Reading R1. Forouzan, “TCP/IP protocol suite”, 4th edition, McGraw-Hill-2010 R2. W.Richard Stevens “TCP/IP illustrated” Volume 2 Pearson Education 2003. R3. Philip M Miller, “TCP/IP: Ultimate Protocol Guide Data Delivery & Routing”, Vol. 1– 2011 R4. Jeffrey L Carrell “Guide to TCP/IP” – CENGAGE Learning, Year: 2013 | |
Evaluation Pattern Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks) End Semester Examination(ESE): 50% (50 marks out of 100 marks)
| |
CS743E03 - SIMULATION AND MODELING (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
objectives: Simulation and Modeling introduces simulation technologies and techniques, provides the foundations for the student to understand computer simulation needs, and to implement and test a variety of simulation and data analysis libraries and programs. This course focuses on what is needed to build simulation software environments, and not just building simulations using pre-existing packages. Simulation languages conceptualize the layers of critical infrastructure networks and Case studies are discussed to build tools and control their results. |
|
Course Outcome |
|
Course Outcomes: CO1: demonstrate the concepts which include the techniques of simulation, major application areas, concept of a system, environment, continuous and discrete system models CO2: apply probability concepts in simulation including discrete and continuous, probability functions, numerical evaluation of continuous probability functions CO3: Developing of Simulation experiments and sampling concepts. CO4: Analyze discrete system and Continues system simulation and study on different simulation languages. CO5: identify the role of simulation studies in practical systems. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
|
|
Systems, modeling, general systems theory, Concept of simulation, Simulation as a decision making tool, types of simulation | |
Unit-2 |
Teaching Hours:9 |
RANDOM NUMBERS
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|
Pseudo random numbers, methods of generating random variables, discrete and continuous distributions, testing of random numbers. | |
Unit-3 |
Teaching Hours:9 |
DESIGN OF SIMULATION EXPERIMENTS
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|
Problem formulation, data collection and reduction, time flow mechanism, key variables, logic flow chart, starting condition, run size, experimental design consideration, Splitting and Sampling Techniques, output analysis and interpretation validation | |
Unit-4 |
Teaching Hours:9 |
SIMULATION LANGUAGES
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|
Systems Models : Deep learning models like ANN and CNN Models and Reinforcement learning models | |
Unit-5 |
Teaching Hours:9 |
CASE STUDIES
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|
CASE STUDIES Development of simulation models using simulation language studied for systems like queuing systems, Production systems, Inventory systems, maintenance and replacement systems and Investment analysis. | |
Text Books And Reference Books: Text Books: T1. Geoffrey Gordon, “System Simulation”, 2nd Edition, Prentice Hall, India, 2011 T2. Narsingh Deo, “System Simulation with Digital Computer, “Prentice Hall, India, 2009 | |
Essential Reading / Recommended Reading Reference Books: R1. Jerry Banks and John S. Carson, Barry L. Nelson, David M. Nicol, “Discrete Event System Simulation”, 3rd Edition, Prentice Hall, India, 2002. R2. Shannon, R.E. “Systems simulation: The art and science”, Prentice Hall, 1975. R3 .Thomas J. Schriber, “Simulation using GPSS”, John Wiley, 1991. | |
Evaluation Pattern CIA Marks 50 ( CIA I-10; MSE-25; CIA III-10; Attendance-5) ESE Marks 50 | |
CS743E04 - SOFTWARE PROCESS AND PROJECT MANAGEMENT (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
To provide basics for various Process and Project management models, also it provide students a systematic approach to initiate, plan, execute, control and close a software project and understanding of the best practices, and techniques used in project management processes, knowledge of ISO 9000 and CMMI, and process improvement techniques. |
|
Course Outcome |
|
CO1: Understand the software process framework and process model. CO2: Demonstrate the importance of stepwise project planning and software estimations CO3: Analyze the various network planning models for activity planning. CO4: Demonstrate skills to monitor the progress of a project. CO5: Apply knowledge on managing people in a software development team. |
Unit-1 |
Teaching Hours:9 |
SOFTWARE PROCESS MATURITY
|
|
Software maturity Framework, Principles of Software Process Change, Software Process Assessment, The Initial Process. | |
Unit-2 |
Teaching Hours:9 |
PROJECT PLANNING AND EFFORT ESTIMATION
|
|
Importance of Software Project Management – Activities Methodologies – Categorization of Software Projects – Stepwise Project Planning- Basics of Software estimation – Effort and Cost estimation techniques – COSMIC Full function points - COCOMO II A Parametric Productivity Mode. | |
Unit-3 |
Teaching Hours:9 |
ACTIVITY PLANNING
|
|
Objectives of Activity planning – Project schedules – Activities – Sequencing and scheduling – Network Planning models – Forward Pass & Backward Pass techniques –Critical path (CRM) method – Precedence Network - PERT technique. | |
Unit-4 |
Teaching Hours:9 |
PROJECT MONITORING AND CONTROL
|
|
Framework for Management and control – Collection of data Project termination –Visualizing progress – Cost monitoring – Earned Value Analysis- Project tracking – Change control- Software Configuration Management. | |
Unit-5 |
Teaching Hours:9 |
STAFFING IN SOFTWARE PROJECTS
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|
Managing people – Organizational behavior – Best methods of staff selection –Motivation – The Oldham-Hackman job characteristic model – Working in teams – Decision making – Team structures – Communications genres – Communication plans. | |
Text Books And Reference Books: T1. Watts S. Humphrey ―Managing the Software Process‖, Pearson Education 2012. T2. Bob Hughes, Mike Cotterell and Rajib Mall: Software Project Management – Fifth Edition, Tata McGraw Hill, New Delhi, 2012 T3. Walker Royce ―Software Project Management Pearson Education 2010. | |
Essential Reading / Recommended Reading R1. Pankaj Jalote ―Software Project Management in Practice, Pearson Education 2010 R2. Chris Kemerer ―Software Project Management Readings and Cases, 2010 R3. Robert K. Wysocki - Effective Software Project Management – Wiley Publication,2011 R4. Gopalaswamy Ramesh - Managing Global Software Projects – McGraw Hill Education (India), Fourteenth Reprint 2013 | |
Evaluation Pattern · Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
| |
CS743E08 - SOFTWARE PROJECT MANAGEMENT (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
The main goal of software development projects is to create a software system with a predetermined functionality and quality in a given time frame and with given costs. For achieving this goal. models are required for determining target values and for continuously controlling these values. This course focuses on principles, techniques, methods & tools for model-based management of software projects. Assurance of product quality and process adherence (quality assurance), as well as experience-based creation & improvement of models (process management). The goals of the course can be characterized as follows. • Understanding the specific roles within a software organization as related to project and process management • Understanding the basic infrastructure competences (e.g., process modeling and measurement) • Understanding the basic steps of project planning, project management. Quality assurance, and process management and their relationships. |
|
Course Outcome |
|
CO1: Explain the specific roles within a Conventional Software Management organization as related to project CO2: Illustrate the purpose and importance of project management from the perspectives of planning, cost, tracking and completion of project. CO3: Summarize a project to develop the scope of work, provide accurate cost estimates and to plan the various activities. CO4: Identify a project to manage project schedule, expenses and resources with the application of suitable protect management tools. CO5: Analyze the resources required for a project to produce a work plan with resource Schedule and compare organization, project structures. |
Unit-1 |
Teaching Hours:9 |
Conventional Software Management
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|
The waterfall model, conventional software Management performance. Evolution of Software Economics: Software Economics. Pragmatic software cost estimation. | |
Unit-2 |
Teaching Hours:9 |
Improving Software Economics
|
|
Reducing Software product size, Improving software processes, improving team effectiveness. Improving automation, Achieving required quality, peer inspections. The old way and the new- The principles of conventional software engineering. Principles of modem software management, transitioning to an iterative process. | |
Unit-3 |
Teaching Hours:9 |
Life cycle phases
|
|
Engineering and production stages, inception. Elaboration, construction, transition phases. Artifacts of the process: The artifact sets. Management artifacts, Engineering artifacts, programmatic artifacts. Model based software architectures: A Management perspective and technical perspective. | |
Unit-4 |
Teaching Hours:9 |
Work Flows of the process
|
|
Software process workflow, Inter trans workflows. Checkpoints of the Process: Major Mile Stones, Minor Milestones, Periodic status assessments. Iterative Process Planning Work breakdown structures, planning guidelines, cost and scheduled estimating, Interaction, planning process, Pragmatic planning. | |
Unit-5 |
Teaching Hours:9 |
Project Control and Process instrumentation
|
|
The server care Metrics, Management indicators, and quality indicators. Life cycle expectations pragmatic Software Metrics, Metrics automation. Tailoring the Process: Process discriminates, Example. Future Software Project Management: Modem Project Profiles Next generation Software economics modem Process transitions. Case Study: The Command Center Processing and Display System. Replacement (CCPDS. R). | |
Text Books And Reference Books: T1. Software Project Management. Walker Royce, Pearson Education 2010. T2. Software Project Management, Bob Hughes & Mike Cotterell, fourth edition, Tate McGraw HD 2012 | |
Essential Reading / Recommended Reading R1. Applied Software Project Management, Andrew SteIbian 8 Jennifer Greene, O’Reilly. 2006 R2. Head First PMP, Jennifer Greene & Andrew Steliman, ORoiHy.2007 R3. Software Engineering Project Management. Richard H. Thayer & Edward Yourdon, second edition, Wiley India, 2004. R4. Ale Project Management, Jim Highsniith. Pearson education, 2004 R5. The art of Project management. Scott Berkun. O’Reilly, 2005. R6. Software Project Management in Practice. Pankaj Jalote. Pearson Educabon,2002. | |
Evaluation Pattern CIA Marks 50 ESE Marks 50 | |
CS744E01 - INFORMATION STORAGE AND MANAGEMENT (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
The course on Information Storage and Management aims at emphasizing the need for Information storage, provides an in depth coverage of technologies in the various phases of designing, building and sustaining an Information Storage System and to provide an overview of various management techniques. |
|
Course Outcome |
|
CO 1: Illustrate the core concepts of information lifecycle and Storage management technologies. CO 2: Interpret the functioning of Physical and logical disk organization. CO 3: Summarize the concept of network storage elements and connectivity. CO 4: Apply disaster recovery principles & techniques with industry management standards. CO 5: Examine the various virtualization technologies in storage. |
Unit-1 |
Teaching Hours:9 |
1 INTRODUCTION TO STORAGE TECHNOLOGY
|
|
Data proliferation and the varying value of data with time & usage, sources of data and states of data creation, Data center requirements and evolution to accommodate storage needs, Overview of basic storage management skills and activities, The five pillars of technology, Overview of storage infrastructure components, Evolution of storage, Information Lifecycle Management concept, Data categorization within an enterprise, Storage and Regulations | |
Unit-2 |
Teaching Hours:9 |
2 STORAGE SYSTEMS ARCHITECTURE
|
|
Intelligent disk subsystems overview, Contrast of integrated vs. modular arrays, Component architecture of intelligent disk subsystems, Disk physical structure components, properties, performance, and specifications, Logical partitioning of disks, RAID & parity algorithms, hot sparing, Physical vs. logical disk organization, protection, and back end management, Array caching properties and algorithms, Front end connectivity and queuing properties, Front end to host storage provisioning, mapping, and operation, Interaction of file systems with storage, Storage system connectivity protocols | |
Unit-3 |
Teaching Hours:9 |
3 INTRODUCTION TO NETWORKED STORAGE
|
|
JBOD, DAS, SAN, NAS, & CAS evolution, Direct Attached Storage (DAS) environments: elements, connectivity, & management, Storage Area Networks (SAN): elements &connectivity, Fibre Channel principles, standards, & network management principles, SAN management principles, Network Attached Storage (NAS): elements, connectivity options, connectivity protocols (NFS, CIFS, ftp), &management principles, IP SAN elements, standards (iSCSI, FCIP, iFCP), connectivity principles, security, and management principles, Content Addressable Storage (CAS): elements, connectivity options, standards, and management principles, Hybrid Storage solutions overview including technologies like virtualization & appliances | |
Unit-4 |
Teaching Hours:9 |
4 INTRODUCTIONS TO INFORMATION AVAILABILITY
|
|
Business Continuity and Disaster Recovery Basics, Local business continuity techniques, Remote business continuity techniques, Disaster Recovery principles & techniques. Managing & Monitoring. Management philosophies (holistic vs. system & component), Industry management standards (SNMP, SMI-S, CIM), Standard framework applications, Key management metrics (thresholds, availability, capacity, security, performance), Metric analysis methodologies & trend analysis, Reactive and proactive management best practices, Provisioning & configuration change planning, Problem reporting, prioritization, and handling techniques, Management tools overview | |
Unit-5 |
Teaching Hours:9 |
5 SECURING STORAGE AND STORAGE VIRTUALIZATION
|
|
Define storage security, List the critical security attributes for information systems, describe the elements of a shared storage model and security extensions, Define storage security domains, List and analyze the common threats in each domain, Identify different virtualization technologies, describe block-level and file level virtualization technologies and processes. | |
Text Books And Reference Books: T1. Information Storage and Management, Storing, Managing, and Protecting Digital Information in Classic, Virtualized, and Cloud Environments, 2nd Edition, EMC Educational Services, Wiley 2012. | |
Essential Reading / Recommended Reading R1. Marc Farley Osborne, “Building Storage Networks”, Tata McGraw Hill., 2001. R2. Robert Spalding, “Storage Networks: The Complete Reference “, Tata McGraw Hill., 2003. R3. Storage Area Network Fundamentals, Meeta Gupta, Pearson Education Limited, 2002 R4. Information Storage & Retrieval Systems Theory & Implementation, Gerald J Kowalski / Mark T Maybury, BS Publications., 2006. R5. Disaster Recovery & Business Continuity - Thejendra BS, Shroff Publishers & Distributors., 2008. R6. Blade Servers & Virtualization - Barb Goldworm / Anne Skamarock, Wiley India Pvt.ltd, 2009. | |
Evaluation Pattern CIA - 50% of the marks obtained out of 100 ESE - 50% of the marks obtained out of 100 | |
CS744E02 - DATA BASE ADMINISTRATION (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
The course will discuss the rationale, current trends and features of modern database practice, also it provides students with the tools and techniques to implement and administer complex database systems including backup,recovery and it equips them with the skills required to develop creative solutions to information system problems using the latest database technologies. |
|
Course Outcome |
|
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
|
|
General Definition of DBA and Security, System Management & Database Design Roles of DBA – DBA Job Classification. Types of Databases: Online Transaction Processing System and Decision Support System Databases, Development, Test & Production Databases. Daily Routine of a DBA. | |
Unit-2 |
Teaching Hours:9 |
ORACLE 10G ARCHITECTURE
|
|
Database Structures: Logical & Physical, Trace Files, Data Files & Tablespaces, Oracle Managed Files. Processes: Interaction between User & Oracle Processes, The Server Process, Background Processes. Memory Structures: SGA, PGA. Oracle Transactions: Anatomy of SQL Transactions. Data Consistency & Concurrency: Database Writer & Write Ahead Protocol, The System Change Number, Undo Management. Backup and Recovery Architecture: User managed, RMAN, Flashback Techniques Data Dictionary and Dynamic Performance Views: Data Dictionary, V$ views, The Oracle Optimizer. Oracle utilities, Automatic Database Management, Advisory Framework. | |
Unit-3 |
Teaching Hours:9 |
DATABASE CREATION, CONNECTIVITY & NETWORKING
|
|
Installing Oracle 10g: Following OFA, System and Owners Pre-Installation Tasks, Installing Software, System Administrator and Oracle Owner’s Post-Installation Tasks, Uninstalling Oracle 10g. Database Creation: Creating SPFILE and pfile, Initialization Parameters, Creating a new Database, Using SPFILE, Starting up and Shutting Down Database. Database Connectivity and Networking: Working of Oracle Network – instance names, global database names, connect descriptors, identifiers and strings, Establishing Connectivity, Oracle Client, Installing the Client, Naming and Connectivity – Local, Easy connect, External and Directory naming methods. | |
Unit-4 |
Teaching Hours:9 |
DATABASE USER MANAGEMENT & DATABASE SECURITY
|
|
Managing Users: Creating, altering and dropping users, Creating user Profiles & Resources, Database Resource Manager, Controlling Access to Data – Roles, Privileges and using Views, Stored Procedures to Manage Privileges, Auditing Database – Standard Auditing, Authentication – Database, External, Centralized user and Proxy Authentication. Database Security Do’s & Don’ts: User Accounts, Passwords, OS authentication, Auditing Database, Granting Appropriate Privileges, Permissions, Application Security. | |
Unit-5 |
Teaching Hours:9 |
DATA LOADING, BACKUP, RECOVERY & DATABASE PERFORMANCE TUNING
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|
Data Loading, Backup & Recovery & Database Performance Tuning Overview of extraction loading and Transformation, Loading Data: Using the SQL Loader Utility, Using External Tables to Load Data. Overview of Common Techniques used for Transforming Data, Introduction to Data Pump Technology – Benefits, Uses and Components of Data Pump. Access method, Data Pump Files, Privileges, Mechanics of Data Pump Job. Backing Up Oracle Databases: Backup Terms, Guidelines, Strategies, Examining Flash Recovery Area – benefits of Flash recovery Area, Looking into Flash Recovery Area, Setting size of Flash Recovery Area Creating Flash Recovery Area, Backing up Flash Recovery Area, RMAN – Benefits, Architecture, Connecting to RMAN. SQL Query Optimization: Approach to Performance Tuning, Optimizing Oracle Query Processing, Cost-based Optimizer, Drawbacks of CBO. SQL Performance Tuning Tools – EXPLAIN PLAN, Autotrace, SQL Trace and TKPROF. Tuning the instance: Introduction, Automatic Tuning vs. Dynamic Views.
Introduction to iSQL*Plus: Installation, configuration, Starting and Stopping iSQL*Plus, Logging into and disconnecting from iSQL*Plus. Case study. | |
Text Books And Reference Books: T1. Ross Mistry, Stacia Misner , “Introducing Microsoft SQL Server 2014”, (2014)T2. Arup Nanda and Steven Fewrstein, “Oracle PL/SQL for DBAs”, O'Reilly Media, Inc.T3. Craig S. Mullins, “Database Administration: The Complete Guide to DBA Practices and Procedures”, Addison-Wesley, 11-Oct-2012T4. Alapati, Sam R., Expert Oracle Database 10g Administration, Springer India Pvt. Ltd., 2005 | |
Essential Reading / Recommended Reading R1. Thomas Kyte ,Darl Kuhn, ”Expert Oracle database Architecture”, Third Edition,2014. R2. Day, John & Craig Van Slyke, “Starting Out with…Oracle”, Dream tech Publication. R3. Loney, Kevin & Koch, George, “Oracle9i The Complete Reference”, Author’s Press/ Dreamtech Publication. | |
Evaluation Pattern CIA=50 ESE=50 | |
CS744E03 - NETWORK STORAGE TECHNOLOGIES (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
The main objective of the course is to expose students to different network storage devices and Identify the need for performance evaluation. It also provides the techniques used for data maintenance and Realizes students with strong virtualization concepts. To develop techniques for evaluating policies for LUN masking, file systems.
|
|
Course Outcome |
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CO1: Recognize the architecture of server centric IT and intelligent disk systems. CO2: Demonstrate I/O techniques and Network Attached Storage. (NAS) CO3: Exhibit the concepts of file systems, storage virtualization with respect to NAS. CO4: Use the concepts of SAN architecture to create a network for storage CO5: Illustrate the software components of SAN with availability, capacity and serviceability. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
|
|
Server Centric IT Architecture and its Limitations; Storage – Centric IT Architecture and its advantages. Case study: Replacing a server with Storage Networks, The Data Storage and Data Access problem; The Battle for size and access. Intelligent Disk Subsystems: Architecture of Intelligent Disk Subsystems; Hard disks and Internal I/O Channels; JBOD, Storage virtualization using RAID and different RAID levels; Caching: Acceleration of Hard Disk Access; Intelligent disk subsystems, Availability of disk subsystems. | |
Unit-2 |
Teaching Hours:9 |
I/O TECHNIQUES
|
|
The Physical I/O path from the CPU to the Storage System; SCSI; Fiber Channel Protocol Stack; Fiber Channel SAN; IP Storage. Network Attached Storage: The NAS Architecture, The NAS hardware Architecture, The NAS Software Architecture, Network connectivity, NAS as a storage system. | |
Unit-3 |
Teaching Hours:9 |
FILE SYSTEM AND NAS
|
|
Local File Systems; Network file Systems and file servers; Shared Disk file systems; Comparison of fiber Channel and NAS. Storage Virtualization: Definition of Storage virtualization; Implementation Considerations; Storage virtualization on Block or file level; Storage virtualization on various levels of the storage Network; Symmetric and Asymmetric storage virtualization in the Network. | |
Unit-4 |
Teaching Hours:9 |
SAN ARCHITECTURE AND HARDWARE DEVICES
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|
Overview, Creating a Network for storage; SAN Hardware devices; The fiber channel switch; Host Bus Adaptors; Putting the storage in SAN; Fabric operation from a Hardware perspective | |
Unit-5 |
Teaching Hours:9 |
SOFTWARE COMPONENTS OF SAN
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|
The switch’s Operating system; Device Drivers; Supporting the switch’s components; Configuration options for SANs. Management: Planning Business Continuity; Managing availability; Managing Serviceability; Capacity planning; Security considerations. | |
Text Books And Reference Books: T1: Ulf Troppens, Rainer Erkens and Wolfgang Muller: Storage Networks Explained, Wiley India,2007 | |
Essential Reading / Recommended Reading R1: Marc Farley: Storage Networking Fundamentals – An Introduction to Storage Devices, Subsystems, Applications, Management, and File Systems, Cisco Press, 2005. R2: Robert Spalding: “Storage Networks - The Complete Reference”, Tata McGraw-Hill, 2003. R3: Richard Barker and Paul Massiglia: “Storage Area Network Essentials A Complete Guide to understanding and Implementing SANs”, Wiley India, 2006. R4: Nigel Poulton, “Data Storage Networking: Real World Skills for the Comp TIA Storage+ Certification and Beyond”, John Wiley & Sons (29 April 2014). R5: Fujitsu Siemens Computers , “An Introduction to the Fundamentals of Storage Technology “ Publisher: Fujitsu Siemens Computers (January 2009) | |
Evaluation Pattern
| |
CS744E04 - NETWORK ADMINISTRATION (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
Course objectives: This syllabus teaches the basics of network planning and Red Hat installation and configuration. Configuring a database server, creating a VNC server, monitoring performance, providing Web services, exploring SELinux security basics, and exploring desktops
|
|
Course Outcome |
|
CO1: . |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
|
|
Introduction to System Administration, The Unix Way, Essential Administrative Tools and Techniques, Startup and Shutdown. System and Network Administration Defined, Duties of the System Administrator, Planning the Network, Standard Installation, Kick start Installation, Exploring the Desktops, System Startup and Shutdown, The File System Explained, Examining the System Configuration Files. | |
Unit-2 |
Teaching Hours:9 |
Network Services
|
|
Network Services, Managing the X Window System, Configuring Printers, TCP/IP Networking, Subnetting, Managing user and groups, Security, managing network services, The Network File System, The Network Information System, connecting to Microsoft and Novell Networks, ADDS, Configuring a Database Server, Creating a VNC Server, Providing Additional Network Services, Optimizing Network Services. | |
Unit-3 |
Teaching Hours:9 |
Internet Services
|
|
Internet Services, Configuring BIND: The Domain Name System, Configuring Mail Services, Configuring FTP Services, configuring a Web Server, Providing Web Services, Optimizing Internet Services. | |
Unit-4 |
Teaching Hours:9 |
System Administration
|
|
System Administration, Upgrading and Customizing the Kernel, Configuring the System at the Command Line, Administering Users and Groups, Installing and Upgrading Software Packages, Backing Up and Restoring the File System, Performance Monitoring, Network hardware, and crimping standards. | |
Unit-5 |
Teaching Hours:9 |
System Security and Problem Solving
|
|
System Security and Problem Solving, Exploring SELinux Security, Implementing Network Security, Troubleshooting and Problem Solving, Case studies. | |
Text Books And Reference Books: Thomas A. Limoncelli, ”The Practice of System and Network Administration”, Addison-Wesley Professional, Third edition, Published Feb 2017. Terry Collings, Kurt Wall, “Red Hat Linux Networking and System Administration”, 3rd Edition Leen Frisch, “Essential System Administration”, 3rd Edition, O'Reilly Media, 2002.
| |
Essential Reading / Recommended Reading Evi Nemeth, Garth Snyder, Trent R. Hein, Ben Whaley, “Unix and Linux System Administration Handbook”, Prentice Hall | |
Evaluation Pattern Weightage for CIA:50 Weightage for ESE:50 | |
CS744E05 - RESEARCH METHODOLOGY (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
•To orient the student to make an informed choice from a large number of alternative methods and experimental designs available. •To enable the student to present a good research proposal. •To familiarize the student with the nature of research and scientific writing •To empower the student with the knowledge and skills they need to undertake a research project, to present a conference paper and to write a scientific article. |
|
Course Outcome |
|
CO1: Explain research, research methods, methodologies and the problems faced by researchers. CO2: Make use of the statistical techniques in scaling, skewness, correlation, and association for data processing. CO3: Identify discrete, continuous and mixed random variables and distribution techniques for interpretation of data. CO4: Examine the large population of data using sampling techniques, variance and covariance methods. CO5: Build appropriate reports with the use of interpretation techniques that illustrates the research results. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
|
|
An Introduction Meaning of Research, Objectives of Research, Motivation in Research, Types of Research, Research approaches, Research Method versus Methodology, Research and Scientific Method, Importance of Knowing How Research is Done, Research Process, Criteria of Good Research, problem Encountered by Researchers in India. Defining the Research Problem: Definition of Research Problem, Selecting the Problem, Necessity of Defining the Problem Technique Involved in Defining a Problem. | |
Unit-2 |
Teaching Hours:9 |
MEASUREMENT AND SCALING TECHNIQUE
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Measurement in Research, Measurement Scales, Sources of Error in Measurement, Tests of Sound Measurement, Technique of Developing Measurement Tools, Scaling, Meaning of Scaling, Scale Classification Bases, Important Scaling Techniques, Scale Construction Techniques. Processing and Analysis of Data: Processing Operations, Some Problems in Processing, Elements /Types of Analysis, Statistics in Research, Measures of Central Tendency, Measures of Dispersion Measures of Asymmetry (Skewness), Measures of Relationship, Partial Correlation, Association in case of Attributes, Other Measures. | |
Unit-3 |
Teaching Hours:9 |
RANDOM VARIABLE
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Introduction, Review of Probability Theory, Definition of a Random Variable, Conditions for a Function to be a Random Variable, Discrete, Continuous and Mixed Random Variables, Distribution and Density functions, Properties, Binomial, Poisson, Uniform, Gaussian, Exponential, Rayleigh, Conditional Distribution, Conditional Density, Properties. | |
Unit-4 |
Teaching Hours:9 |
SAMPLING FUNDAMENTALS
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Need for Sampling, Some Fundamental Definitions, Central Limit Theorem, Sampling Theorem, Sandler’s A-test, Concept of Standard Error, Estimation, Estimating the Population Mean, Estimating the Population Proportion, Sample size and its Determination, Determination of Sample Size through the Approach, Based on Precision Rate and Confidence Level, Determination of Sample Size through the Approach, Based on Bayesian Statistics. Analysis of Variance and Covariance: Analysis of variance (ANOVA), basic principles, technique, setting up analysis of variance table, short cut method for one- way ANOVA, coding method, two-way-ANOVA, ANOVA in Latin-Square-Design, Analysis of Co-variance (ANOCOVA), technique, assumption in ANOCOVA. | |
Unit-5 |
Teaching Hours:9 |
INTERPRETATION AND REPORT WRITING
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Meaning Of Interpretation, Technique of Interpretation: Precaution in Interpretation, Significance of Report Writing, Different Steps in Writing Report, Layout of the Research Report, Types of Reports, Oral Presentation, Mechanics of Writing a Research Report, Precautions for Writing a Research Report, Research report writing using Latex. Case study | |
Text Books And Reference Books: 1. Kothari C.R., Research Methodology – Methods and Techniques, New Age International, New Delhi, (reprint 2011) 2. Montgomery, Douglas C., Design and Analysis of Experiments, Willey India, 8th Edition, ISV, ISBN: 9788126540501. 3. Montgomery, Douglas C. & Runger, George C., Applied Statistics & Probability for Engineers, Wiley India, 6th Edition, 2016. | |
Essential Reading / Recommended Reading 1. Krishnaswamy, K.N. Sivkumar, Appa Iyer and Mathiranjan M., Management Research Methodology: Integration of Principles, Method and Techniques, Pearson Education, New Dehli, 2009. 2. Charlie Catlett, Wolfgang Gentzsch, Lucio Grandinetti, Gerhard Joubert, and José Luis Vasquez-Poletti, Cloud computing and big data, Published/Distributed: Amsterdam: Washington, DC: IOS Press, 2013. 3. Kirsty Williamson and Graeme Johanson, "Research Methods: Information, Systems, and Contexts", Second Edition, Elsevier Ltd., 2018. | |
Evaluation Pattern ●Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks) ●End Semester Examination(ESE) : 50% (50 marks out of 100 marks) | |
CS745E01 - QUANTUM COMPUTING (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Sound knowledge and understanding of the fundamentals of Quantum Computing, Concepts in quantum computation with examples, building blocks of Quantum Computers, Concepts, applications and limitations of Quantum operations, basic concepts in quantum error correction and fault tolerant quantum computing. |
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Course Outcome |
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Unit-1 |
Teaching Hours:9 |
FUNDAMENTAL CONCEPTS
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Global Perspectives, Linear algebra and Dirac notation, , Quantum Bits, Quantum Computation, Properties of Quantum Algorithms, Quantum Information, Postulates of Quantum Mechanisms | |
Unit-2 |
Teaching Hours:9 |
QUANTUM COMPUTATION
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|
Quantum Gates and Quantum Circuits, Quantum States, Representation of Quantum States, Control Operations, Measurement, Simulation of Quantum Systems, Quantum Fourier transform, Quantum Phase estimation, Quantum search algorithms, Quantum counting Algorithms, Models of Computation, Analysis of Computational Problems. | |
Unit-3 |
Teaching Hours:9 |
QUANTUM COMPUTERS
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Classical Noise and Markov Processes, Quantum noise and Quantum Operations - Representations, Examples, Applications of Quantum operations, Limitations of the Quantum operations formalism, Distance Measures for Quantum information. | |
Unit-4 |
Teaching Hours:9 |
QUANTUM ERROR CORRECTION
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Introduction, The Shor code, Theory of Quantum Error – Correction, Constructing Quantum Codes, Stabilizer codes, Fault – Tolerant Quantum Computation, Entropy and information – Shannon Entropy, Basic properties of Entropy, Von Neumann, Strong Sub Additivity, Data Compression, Entanglement as a physical resource. Case study. | |
Unit-5 |
Teaching Hours:9 |
Quantum Cryptography
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Classical Cryptography - Symmetrical Cryptosystem Asymmetrical Cryptosystem, Quantum Key Distribution - NoCloning Theorem, The BB84 Protocol, The Ekert Protocol, RealWorld Implementation - Polarisation Encoding, Polarisation Entanglement, The ”Venus von Willendorf” Experiment. | |
Text Books And Reference Books: 1. Michael A. Nielsen. & Issac L. Chiang, “Quantum Computation and Quantum Information”, 10th Anniversary edn, Cambridge University Press, 2010 | |
Essential Reading / Recommended Reading R1. Mika Hiravensalo, “Quantum computing” II edition, Springer- 2004
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Evaluation Pattern Continuous Internal Assessment - 50% (50 marks out of 100) End Semester Exam - 50% (50 marks out of 100) | |
CS745E02 - MOBILE COMPUTING (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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At the end of the course, the student should understand to provide basics for various techniques in Mobile Communications and Mobile Content services. To learn the basics of wireless voice and data communications technologies. To build working knowledge on various telephone and satellite networks. To study the working principles of wireless LAN and its standards. To build knowledge on various mobile computing algorithms. To build skills in working with wireless application protocols to develop mobile content applications.
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Course Outcome |
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CO1: Demonstrate basis of wireless technology and media access schemes for classical systems CO2: Present different wireless communication systems and to show how they transfer data between communication partners. CO3: Illustrate MAC Layer Protocols for wireless communication. CO4: Compare the performance of different routing algorithms supported by mobile communication CO5: Organize TCP performance and WAP features in Mobile environment. |
Unit-1 |
Teaching Hours:9 |
WIRELESS COMMUNICATION FUNDAMENTALS
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Introduction–Wirelesstransmission–Frequenciesforradio transmission – Signals – Antennas – Signal Propagation – Multiplexing – Modulations – Spread spectrum – MAC – SDMA – FDMA – TDMA – CDMA – Cellular Wireless Networks.
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Unit-2 |
Teaching Hours:9 |
TELECOMMUNICATION NETWORKS
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Telecommunication systems – GSM – GPRS – DECT – UMTS – IMT- 2000 – Satellite Networks - Basics – Parameters and Configurations – Capacity Allocation – FAMA and DAMA – Broadcast Systems – DAB - DVB.
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Unit-3 |
Teaching Hours:9 |
WIRLESS LAN
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Wireless LAN – IEEE 802.11 - Architecture – services – MAC – Physical layer – IEEE 802.11a - 802.11b standards – HIPERLAN – Blue Tooth. | |
Unit-4 |
Teaching Hours:9 |
MOBILE NETWORK LAYER
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Mobile IP – Dynamic Host Configuration Protocol - Routing – DSDV – DSR – Alternative Metrics.
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Unit-5 |
Teaching Hours:9 |
TRANSPORT AND APPLICATION LAYERS
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Traditional TCP – Classical TCP improvements – WAP, Case Study. | |
Text Books And Reference Books: T1: Jochen Schiller, “Mobile Communications”, PHI/Pearson Education, Second Edition, Reprint edition 2012. T2: William Stallings, “Wireless Communications and Networks”, PHI/Pearson Education, 2009. (Unit I Chapter – 7&10-Unit II Chap 9) | |
Essential Reading / Recommended Reading R1: Kaveh Pahlavan, Prasanth Krishnamoorthy, “Principles of Wireless Networks”, PHI/Pearson Education, 2003. R2: Uwe Hansmann, Lothar Merk, Martin S. Nicklons and Thomas Stober, “Principles of Mobile Computing”, Springer, New York, 2003. R3: Hazysztof Wesolowshi, “Mobile Communication Systems”, John Wiley and Sons Ltd, 2002.
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Evaluation Pattern ●Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks) ●End Semester Examination(ESE) : 50% (50 marks out of 100 marks) | |
CS745E05 - CLOUD COMPUTING (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Cloud computing is a model for enabling ubiquitous, convenient, on-demand access to a shared pool of configurable computing resources. Cloud computing paradigm possesses tremendous momentum but its unique aspects exacerbate security and privacy challenges. Cloud computing enables increasing number of IT services to be delivered over the Internet. The cloud platform enables business to run successfully without dedicated hardware, software and services. |
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Course Outcome |
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CO1: Explain the fundamentals of Cloud computing and Cloud platforms in Industry. CO2: Demonstrate Cloud Computing architecture, technologies, various platforms with respect to platforms, services, network, security and applications CO3: Experiment with Cloud platforms using Aneka and programming applications. CO4: Illustrate the technologies for Data-intensive computing. CO5: Apply Cloud based solutions for Industry platforms and new developments. |
Unit-1 |
Teaching Hours:9 |
Introduction
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Cloud Computing at a Glance, The Vision of Cloud Computing, Defining a Cloud, A Closer Look, Cloud Computing Reference Model, Characteristics and Benefits, Challenges Ahead, Historical Developments, Distributed Systems, Virtualization, Web 2.0, Service-Oriented Computing, Utility-Oriented Computing, Building Cloud Computing Environments, Application Development, Infrastructure and System Development, Computing Platforms and Technologies, Amazon Web Services (AWS), Google AppEngine, Microsoft Azure | |
Unit-2 |
Teaching Hours:9 |
Cloud Computing Architecture
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Introduction, Cloud Reference Model, Architecture, Infrastructure/Hardware as a Service, Platform as a Service, Software as a Service, Types of Clouds, Public Clouds, Private Clouds, Hybrid Clouds, Community Clouds, Economics of the Cloud, Open Challenges, Cloud Definition, Cloud Interoperability and Standards Scalability and Fault Tolerance Security, Trust, and Privacy Organizational Aspects. | |
Unit-3 |
Teaching Hours:9 |
Concurrent Computing
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Introducing Parallelism for Single Machine Computation, Programming Applications with Threads, What is a Thread?, Thread APIs, Techniques for Parallel Computation with Threads, Multithreading with Aneka, Introducing the Thread Programming Model, Aneka Thread vs. Common Threads, Programming Applications with Aneka Threads, Aneka Threads Application Model. | |
Unit-4 |
Teaching Hours:9 |
Data Intensive Computing
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What is Data-Intensive Computing?, Characterizing Data-Intensive Computations, Challenges Ahead, Historical Perspective, Technologies for Data-Intensive Computing, Storage Systems, Programming Platforms, Aneka MapReduce Programming, Introducing the MapReduce Programming Model, Example Application. | |
Unit-5 |
Teaching Hours:9 |
Cloud Platforms in Industry
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Amazon Web Services, Compute Services, Storage Services, Communication Services, Additional Services, Google AppEngine, Architecture and Core Concepts, Application Life-Cycle, Cost Model, Observations, Microsoft Azure, Azure Core Concepts, SQL Azure, Windows Azure Platform Appliance. | |
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) End Semester Examination (ESE) : 50% (50 marks out of 100 marks) | |
CS781 - INTERNSHIP - II (2020 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:1 |
Course Objectives/Course Description |
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Internships are short-term work experiences that will allow a student to observe and participate in professional work environments and explore how his interests relate to possible careers. They are important learning opportunities through industry exposure and practices. Course Objectives: •Identify how the internship relates to their academic courses and preferred career path •Integrate existing and new technical knowledge for industrial application •Understand lifelong learning processes through critical reflection of internship experiences. •Articulate their experience and skills to potential employers |
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Course Outcome |
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CO1: Design solutions to real time complex engineering problems using the concepts of Computer Science and Information Technology through independent study. CO2: Demonstrate teamwork and leadership skills with professional ethics. CO3: Prepare an internship report in the prescribed format and demonstrate oral communication through presentation of the internship work. |
Unit-1 |
Teaching Hours:30 |
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INTERNSHIP POLICY, GUIDELINES AND PROCEDURES
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1.The student shall undergo an Internship for30 days starting from the end of 4th semester examination and completing it during the initial period of 5th semester. 2.The department shall nominate a faculty as a mentor for a group of students to prepare and monitor the progress of the students. 3. The students shall report the progress of the internship to the mentor/guide at regular intervals and may seek his/her advise. 4. The Internship evaluation will be completed by the end of 5th semesters. 5. The students are permitted to carry out the internship outside India with the following conditions, the entire expenses are to be borne by the student and the University will not give any financial assistance. 6. Students can also undergo internships arranged by the department during vacation. 7. After completion of Internship, students shall submit a report to the department with the approval of both internal and external guides/mentors. 8. There will be an assessment for the internship for 1 credit, in the form of report assessment by the guide/mentor and a presentation on the internship given to department constituted panel. | ||||||||
Text Books And Reference Books: Nil | ||||||||
Essential Reading / Recommended Reading . | ||||||||
Evaluation Pattern Maximum Marks = 50(Only credit will be displayed in the score card) Passing marks 40% min Internship assessment will be carried out based on the following parameters, during the 5th semester as a single Presentation evaluation.
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CS782 - PROJECT WORK PHASE I (2020 Batch) | ||||||||
Total Teaching Hours for Semester:120 |
No of Lecture Hours/Week:8 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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To perform a task involving research or design, that is carefully planned to achieve a particular aim. To learn modular programming - analyse problems, design solutions, learn new tools and implement the system as a team/ individual. |
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Course Outcome |
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CO1: Design engineering solutions to complex real world problems using research literature for societal applications through independent study. CO2: Use appropriate hardware and software depending on the nature of the project with an understanding of their limitations. CO3: Demonstrate teamwork and leadership skills with professional ethics and prepare a project report in the prescribed format. CO4: Understand the impact of the developed projects on environmental factors. CO5: Demonstrate project management skills including handling the finances in doing projects for given real world societal problems. |
Unit-1 |
Teaching Hours:120 |
Project
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Literature survey, Requirment analysis, Design and Development of the project | |
Text Books And Reference Books: NA | |
Essential Reading / Recommended Reading . | |
Evaluation Pattern ●Continuous Assessment: 50 marks. ●End Semester Examination (project report evaluation and viva-voce): 50 marks. ●The continuous assessment and End Semester Examinations marks for Project Work and the Viva-Voce Examination will be distributed as indicated below. | |
CSHO731AIP - COMPUTER VISION (2020 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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· To provide an introduction to concepts in Computer Vision including fundamental Image Processing Operations, Image enhancement, edge detection, Texture, boundary, shape and motion analysis, object segmentation, image transformation and 3D vision. To provide practical experience in implementing Computer Vision algorithms. |
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Course Outcome |
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CO1: Experiment with basic image processing operations ? filtering, Morphology and thresholding. CO2: Develop programs for the detection of edges, corners, points of interest and for texture analysis CO3: Experiment with shape analysis algorithms. CO4: Apply object segmentation and shape modelling for object detection and extraction. CO5: Construct Computer Vision solution for a given problem |
Unit-1 |
Teaching Hours:9 |
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Unit-1
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Images and imaging operations – Image filtering and morphology – Thresholding. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Unit-2
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Edge detection, Corner, interest point, and invariant feature detection – Texture analysis | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Unit-3
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Binary shape analysis – Boundary pattern analysis –Line, Circle, and Ellipse detection – generalized Hough transform | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Unit-4
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Object Segmentation and shape models - The three Dimensional world – Perspective n-point problem – invariants and perspective | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Unit-5
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Image transformation and camera calibration – Motion. Case studies – Face detection and recognition, surveillance , In-vehicle vision systems | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: T1. E.R. Davies, Computer Vision: Principles, Algorithms, Applications, Learning, 5e, AP, 2018 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading R1. Ponce Jean & Forsyth David , Computer Vision: A Modern Approach, 2e, Pearson, 2015 R2. Richard Szeliski, Computer vision: Algorithms and Applications, 1e, Springer, 2010 R3. J. R. Parker, Algorithms for Image Processing and Computer Vision, 2e, Wiley, 2010 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
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CSHO731DAP - WEB ANALYTICS (2020 Batch) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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This Web Analytics course covers fundamental concepts of web analytics and dives deep into web, social and content and analytics, illustrating common analytical scenarios and how to use popular web analytics tools used by marketers across the major industry domains. The course approaches web analytics from a strategic and practical perspective, showcasing techniques for using Google Web analytics and other platforms and tools. You’ll keep pace with the most important analytics trends and prepare for a career in web and digital analytics. |
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Course Outcome |
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CO1: Demonstrate the fundamental concepts of web analytics. CO2: Illustrate various competitive intelligence analysis in web analytics. CO3: Analyze and Examine Social, Mobile and Video Emerging Analytics. CO4: Examine working of Google Analytics and creating an Implementation Plan. CO5: Develop Google Analytics Accounts and Profiles. |
Unit-1 |
Teaching Hours:9 |
Web Analytics 2.0
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The Bold New World of Web Analytics 2.0 State of the Analytics Union, State of the Industry, Rethinking Web Analytics: Meet Web Analytics 2.0 The Awesome World of Clickstream Analysis: Metrics Eight Critical Web Metrics:Visits and Visitors, Time on Page and Time on site, Bounce Rate, Exit Rate, Conversion rate, Engagement. Web Metrics Demystified, Strategically-aligned Tactics for Impactful Web Metrics | |
Unit-2 |
Teaching Hours:9 |
Competitive Intelligence Analysis
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Competitive Intelligence Analysis CI Data Sources: Toolbar Data, Panel Data, ISP(Network) Data, Search Types and Secrets Website Traffic Analysis: Comparing Long Term Traffic Trends, Analyzing Competitive Sites Overlap and Opportunities, Analyzing Referrals and Destinations Search and Keyword Analysis Top Keywords Performance Trend, Geographic Interest and Opportunity Analysis, Related and Fast Rising searches, Share-of Shelf Analysis, Competitive Keyword Advantage Analysis, Keyword Expansion Analysis | |
Unit-3 |
Teaching Hours:9 |
Emerging Analytics: Social, Mobile and Video
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Emerging Analytics: Social, Mobile and Video Measuring the New Social Web: The Data Challenge, The Content Democracy Evaluation, The Twitter Revolution Analyzing Offline Customer Experiences(applications), Analyzing mobile customer Experience: Mobile Data Collection, Mobile Reporting and Analysis Measuring the success of Blogs: Raw Author Contribution, Holistic Audience growth, Citations and Ripple Index, Cost of Blogging, Benefit(ROI) from Blogging Quantifying the Impact of Twitter: Growth in Number of Followers, Message Amplification, Click-Through Rates and Conversions, Conversation Rate, Emerging Twitter Metrics Analyzing Performance of Videos Data Collection for Videos, Key Video Metrics and Analysis, Advanced Video Analysis | |
Unit-4 |
Teaching Hours:9 |
Case Study: Google Analytics- Part 1
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Case Study: Google Analytics- Part 1 Defining Web Analytics, What Google Analytics Contributes, How Google Analytics Fits in the Analytics Ecosystem. Creating An Implementation Plan: Gather Business Requirements, Analyze and Document Website Architecture, Create an account and configure your profile, Configure the tracking code ad tag pages, Tag Marketing Campaigns, Create Additional User Accounts and Configure Reporting ,Perform operational Configuration Steps Under the Covers: How Google Analytics works Data Collection and Processing, Reports, About the tracking code, Understanding Page views. | |
Unit-5 |
Teaching Hours:9 |
Case Study: Google Analytics- Part 2
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Case Study: Google Analytics- Part 2 Tracking Visitor Clicks, Outbound Links and Non HTML Files About the Tracking Cookies Google Analytics Accounts and Profiles Google Analytics Accounts, Creating a Google Analytics Account: Creating Additional Profiles, Access Levels, All about Profiles: Basic Profile Settings, Profile Name, Website URL, Time Zone, Default Page, Exclude URL Query Parameters, E-commerce settings, Tracking On-site Search, Applying Cost Data. Analyze Website Visitors with Google Analytics Segments: Define segments | |
Text Books And Reference Books: Text Books:
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Essential Reading / Recommended Reading Reference Books:
Online Resources: | |
Evaluation Pattern Continuous Internal Assessment (CIA): 70% (70 marks out of 100 marks) End Semester Examination (ESE): 30% (30 marks out of 100 marks) | |
CSHO781AIP - AI PROJECT/ MOOC COURSE/ CERTIFIED COURSE (2020 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Outcome |
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CO 1: Design engineering solutions to complex real world problems using research literature for societal applications through independent study. CO 2: Use appropriate hardware and software depending on the nature of the project with an
understanding of their limitations. CO 3: Demonstrate teamwork and leadership skills with professional ethics and prepare a project report in the prescribed format CO 4: Understand the impact of the developed projects on environmental factors CO 5: Demonstrate project management skills including handling the finances in doing projects for given real world societal problems |
Unit-1 |
Teaching Hours:120 |
1
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Through this capstone project students will get an opportunity to apply the knowledge and skills in data analytics that they have gained. To test the skills in data analysis, data visualization, data wrangling, regression, machine learning etc. To learn modular programming - analyse problems, design solutions, learn new tools and implement the system as a team/ individual. | |
Text Books And Reference Books: Based on the project the reference materials will be suggested | |
Essential Reading / Recommended Reading Based on the project the additional reference materials will be suggested. | |
Evaluation Pattern
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CSHO781DAP - DA PROJECT / CERTIFICATE COURSES (2020 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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• Through this capstone project students will get an opportunity to apply the knowledge and skills in data analytics that they have gained. • To test the skills in data analysis, data visualization, data wrangling, regression, machine learning etc. • To learn modular programming - analyse problems, design solutions, learn new tools and implement the system as a team/ individual |
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Course Outcome |
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CO1: Design engineering solutions to complex real world problems using research literature for societal applications through independent study. CO2: Use appropriate hardware and software depending on the nature of the project with an understanding of their limitations.
CO3: Demonstrate teamwork and leadership skills with professional ethics and prepare a project report in the prescribed format.
CO4: Understand the impact of the developed projects on environmental factors. CO5: Demonstrate project management skills including handling the finances in doing projects for given real world societal problems |
Unit-1 |
Teaching Hours:75 |
Course Description and Course Objectives
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Through this capstone project students will get an opportunity to apply the knowledge and skills in data analytics that they have gained. To test the skills in data analysis, data visualization, data wrangling, regression, machine learning etc. To learn modular programming - analyse problems, design solutions, learn new tools and implement the system as a team/ individual. | |
Text Books And Reference Books: Based on the project the reference materials will be suggested | |
Essential Reading / Recommended Reading Based on the project the additional reference materials will be suggested. | |
Evaluation Pattern Continuous Internal Assessment: 50 Marks End Semester Examination: 50 Marks | |
ME761E03 - BASIC AUTOMOBILE ENGINEERING (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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The objective of this course is to impact knowledge to students in various systems of Automobile Engineering and to learn the fundamental principles, construction and auxiliary systems of automotive engines. |
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Course Outcome |
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Upon completion of this course, the students will be able to CO1: To describe chassis, body and engine components of automobile. CO2: To demonstrate knowledge of transmission, cooling and lubrication systems. CO3: To demonstrate knowledge of engine injection and ignition systems. CO4: To demonstrate knowledge of steering, brakes and suspension systems. CO5: To describe environmental impact of emissions from vehicles and methods for controlling it. |
Unit-1 |
Teaching Hours:9 |
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Engine
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Engine classifications, number of strokes, cylinders, types of combustion chambers for petrol and diesel engines, valves, valve arrangements and operating mechanisms, piston, design basis, types, piston rings, firing order, fly wheel. | |||||||||||||||||||||||||||||||||||||||||
Unit-1 |
Teaching Hours:9 |
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Introduction
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Classification of vehicles, options of prime movers, transmission and arrangements. | |||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Carburettors and Injection Systems
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carburetors, fuel injection systems for diesel and petrol engines, electronic fuel injection, super chargers, muffers. | |||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Fuel Supply Systems
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Petrol and diesel engines, fuel pumps, Mechanical and electrical diaphragm pumps, air and fuel filters. | |||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Cooling and Lubrication system for IC Engines
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Necessity, methods of cooling, air cooling, water cooling, components of water cooling systems, Objective of lubrication, requirements of lubricant, types of lubricant, various systems of engine lubrication. | |||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Electrical System
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Ignition system, distributor, electronic ignition, magneto, dynamo, alternator, regulator, starting motor, introduction to various accessories, typical wiring diagram.
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Unit-4 |
Teaching Hours:9 |
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Transmission System
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Introduction to single plate clutch, wet and dry type, clutch actuating mechanisms, study of clutch components, fluid fly wheel. Gear box , Theory, four speed and five speed sliding mesh, constant mesh and synchromesh type, selector mechanism, automatic transmission, overdrive, transfer box four wheel drive, torque converter, propeller shaft. | |||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Chassis
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Introduction of chassis, classification, conventional construction, frameless construction, introduction to vehicle dimensions. | |||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Suspension System
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Systems, springs, shock absorbers, axles, front and rear, different methods of floating rear axle, front axle and wheel alignment, types of rims and tyres. | |||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Steering System
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Steering mechanisms, types of brakes and brake actuation mechanisms. | |||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books:
1. Kripal Singh,“Automobile Engineering”, Vol.-1 & 2, Standard publisher distributors 2015. 2. Joseph Heitner,“Automotive Mechanics”, East-West student edition 2014. | |||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading 1. Crouse. W.H. and Angling, D.L “Automobile Mechanics”2009. 2. Judge, A.W ,“Automobile Electrical System”. 3. K.k.Ramalingam,“Automobile engineering”, scitech publications 2001. | |||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
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ME761E04 - SMART MATRIALS AND APPLICATIONS (2020 Batch) | |||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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This interdisciplinary course not only gives an overview of the smart materials and its applications, but also gives an in-depth understanding of the issues involved. It begins by answering the important question: why miniaturize? This is followed by a quick summary of a variety of sensors, actuators, and systems. It then presents a comprehensive description of micro fabrication. This is followed by a detailed discussion of mechanics of solids as it pertains to micro and smart systems. While this part may be viewed as strength of materials and design, an effort is made to relate this to micro devices and discuss such topics as residual stress and stress gradients, lumped modelling using energy methods, anticlastic curvature, etc. |
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Course Outcome |
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CO1: explain the overview of Smart materials. {L1, L2}, {PO1, PO2, PO9} CO2: Explaining the principles of sensing and actuations systems. {L1, L2}, {PO1, PO2, PO9} CO3: Evaluating techniques on control design and optics systems using smart materials {L1, L2}, {PO1, PO2, PO9} CO4: Compute response of an electro mechanical smart system using finite element method. {L1, L2}, {PO1, PO2, PO9} CO5: Incorporate basic knowledge of micro systems and its applications. {L1, L2}, {PO1, PO2, PO9} |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION
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Characteristics of composites and ceramics materials, Dynamics and controls, cconcepts, Electro-magnetic materials and shape memory alloys-processing and characteristics | |||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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SENSING AND ACTUATION
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Principals of electromagnetic, acoustics, chemical and mechanical sensing and actuation, Types of sensors and their applications, their compatibility writer conventional and advanced materials, signal processing, principals and characterization. | |||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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OPTICS AND ELECTROMAGNETIC
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Principals of optical fiber technology, characteristics of active and adaptive optical system and components, design and manufacturing principles. | |||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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CONTROL DESIGN
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Design of shape memory alloys, Types of MR fluids, Characteristics and application, principals of MR fluid value designs, Magnetic circuit design, MR Dampers, Design issues. | |||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Micro systems
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Overview of Micro and smart systems, Processing of Sensors, Actuators and micro structures, Applications in diverse fields including Biomedical, Defence, Automobile and Aerospace Engineering. | |||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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MICRO FABRICATION PROCESSES
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Overview of Micro Machining Technologies, miniaturization, conventional and silicon micro machining techniques, Ultrasonic machining, sandblasting, laser ablation, spark erosion, and photo lithography. | |||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: T1. G. K. Anantha Suresh, “Micro and Smart Systems”, Wiley India Pvt. Ltd., 2010. T2. Banks HT, RC Smith, Y Wang, Massow S A, ‘Smart Materials and Structures’, Paris 1996 | |||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading R1. G. K. Anantha Suresh, “Micro and Smart Systems”, Wiley India Pvt. Ltd., 2010. R2. G. K. Anantha Suresh, K. J. Vinoy, S. Gopalakrishnan, K. N. Bhat, V. Kasudev Aatre, “Micro and Smart Systems: Technology and Modeling”, John Wiley & Sons, 2012. R3. Tai-Ran Hsu, “MEMS and Microsystems: Design and Manufacture”, Tata McGraw Hill Education Private Limited, 2002. R4. ‘M V Gandhi and B S Thompson Chapmen & Hall , ‘Smart Materials and Structures’, London, 1992 (ISBN : 0412370107).
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Evaluation Pattern
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NCCOE2 - NCC2 (2020 Batch) | |||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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Course Outcome |
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CO1: Demonstrate Foot drill, Rifle Drill and ceremonial Drill(L3) CO2: Illustrate the importance and need for National integration(L2) CO3: Make use of Leadership traits to organize critical decisions (L3) CO4: Relate to Social Issues and contribute to the Environmental sustainability (L2) C05: Utilize Community Development skills for social wellbeing(L3) |
Unit-1 |
Teaching Hours:9 |
Drill
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Foot Drill – Marching Salute- Flight formation- Slow march- Rifle Drill- Guard of honor- Present Arm. | |
Unit-2 |
Teaching Hours:9 |
National Integration
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Importance & Necessity-Factors Affecting National Integration- Unity in Diversity & Role of NCC in Nation Building- Threats to National Security. | |
Unit-3 |
Teaching Hours:9 |
Leadership
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Leadership Defined - Ways of Conceptualizing Leadership -Definition and Components- Leadership Described -Trait Versus Process Leadership - Assigned Versus Emergent Leadership -Leadership and Power - Leadership and Coercion- Leadership and Management- The Trait Description Case Studies: Shivaji, Jhasi Ki Rani | |
Unit-4 |
Teaching Hours:9 |
Social Issues and the Environment
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Resettlement and rehabilitation of people - environmental ethics: issues and possible solutions - nuclear accidents and nuclear holocaust -wasteland reclamation consumerism and waste products. Environment protection act air (prevention and control of pollution) act 194- water (prevention and control of pollution) ACT 196 | |
Unit-5 |
Teaching Hours:9 |
Community Development
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Contribution of Youth- Social Evils- Protection of Children & Women Safety- Cyber and Mobile Security Awareness - Hygiene and Sanitation (Personal and Camp). | |
Text Books And Reference Books: Airwing Cadet Handbook, Common Subject SD/SW, Maxwell Press, 2015. | |
Essential Reading / Recommended Reading Textbook of Environmental Studies for Undergraduate Courses, Erach Barucha, Orient Black swan Pvt Ltd, 2nd edition, march 2021 | |
Evaluation Pattern 1. The assessment will be carried out as overall internal assessment at the end of the semester for 100 marks based on the following.
· Each cadet will appear for ‘C’ Certificate exam which is centrally conducted by the Ministry of Defense, NCC directorate. The Total marks will be for 350. · Each cadets score will be normalized to a maximum of 100 marks based on the overall marks Secured by each cadet.
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PH736OE1 - NANO MATERIALS AND NANOTECHNOLOGY (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course Description: This course deals with overall aspects of Nano materials and Nanotechnology, different types of nano materials, synthesis, properties and their applications in different aspects of technology frontiers like space, electrical & electronics, industries, medicals, automotive etc. This course will also serve as a prerequisite for post graduate and research.
Course Objective: · To distinguish between the concept of bulk and nanomaterials. · To understand the science of different synthesis methods and characterization of nanomaterials. · To analyze physical and chemical properties of different types of nanomaterials. · To understand various types of application of nanotechnology in engineering and sciences. |
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Course Outcome |
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CO1: Students will be able to explain the basics of Nanomaterials {L2} {PO1, PO2} CO2: Students will be able to outline the science of different synthesis methods and characterization of nanomaterials. {L2} { PO1, PO2} CO3: Students will be able to analyze physical and chemical properties of different types of nanomaterials {L4} { PO1, PO2, PO3} CO4: Students will be able to explain the basic concepts of Carbon nano tubes{L2} {PO1, PO2} CO5: Students will be able to illustrate the applications of nanotechnology in engineering and sciences. {L3} { PO1, PO2, PO3, PO4}
close |
Unit-1 |
Teaching Hours:8 |
Introduction
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Definition of Nano, Atomic Structure and atomic size, Emergence and challenges of nanoscience and nanotechnology, influence of nano over micro/macro, size effects and crystals, large surface to volume ratio, surface effects on the properties, One dimensional, Two dimensional and Three dimensional nanostructured materials, Examples of nano systems | |
Unit-2 |
Teaching Hours:9 |
Synthesis of nanomaterials
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Bottom-up approaches for nanostructure fabrication: Sol-gel method, Top down approaches for nanostructure fabrication: Ball milling, Lithography, melt quenching and annealing. Self Assembled Monolayers (SAM), Chemical Vapour Deposition (CVD), Spin coating. | |
Unit-3 |
Teaching Hours:9 |
Characterization of nanomaterials
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X-ray diffraction, particle size analyses using-Scherer`s formula, Scanning Electron Microscope (SEM) –Field Emission Scanning Electron Microscope (FESEM)- Atomic Force Microscopy (AFM ), Transmission Electron Microscopy (TEM). | |
Unit-4 |
Teaching Hours:9 |
Nanomaterials
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Microemulsions, colloidal material, nanocomposite polymers, Metal Oxide Nanoparticle, Semiconductor nanostructures, Polymer membranes, carbon nanotubes (CNT’s), single-and multi-walled CNT – nanowires, graphene, Nanomagnetic materials | |
Unit-5 |
Teaching Hours:10 |
Applications
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Molecular electronics and nanoelectronics, environmental applications, super hydrophilic hydrophobic surfaces, self-cleaning surfaces, membrane-based application, polymer based application. Nanotechnology based water treatment & purification. Catalytic applications-Fuel Cells.Carbon Nanotubes for energy storage. | |
Text Books And Reference Books: 1. Processing & properties of structural naonmaterials ‐Leon L. Shaw, Nano chemistry: A Chemical Approach to Nanomaterials, Royal Society of Chemistry, Cambridge UK 2005. 2. Nanoparticles: From theory to applications – G. Schmidt, Wiley Weinheim 2004. 3. Advances in Nanotechnology and the Environment, Juyoung Kim, CRC Press, Taylor and Francis Group. 4. W. Gaddand, D.Brenner, S.Lysherski and G.J.Infrate (Eds), Handbook of nanoscience, Engg. and Technology, CRC Press,2002. 5. G. Cao, Naostructures and Nanomaterials: Synthesis, properties and applications, Imperical College Press, 2004. 6. Ghuzang G.Cao, Naostructures and Nanomaterials: Synthesis, properties and applications, Imperical College Press, 2004 | |
Essential Reading / Recommended Reading 1. Chemistry of nano materials: Synthesis, properties and applications by C. N. R. Rao et. al. 2. Environmental Chemistry for a Sustainable World, Volume 1: Nanotechnology and Health RiskEditors: Lichtfouse, Schwarzbauer, Robert. 3. C.N.R. Rao, A. Muller, A.K.Cheetham (Eds), The chemistry of nanomaterials: Synthesis, properties and applications, Wiley VCH Verlag Gmbh&Co, Weinheim, 2004. | |
Evaluation Pattern CIA I - 20 Marks - 2 components
CIA II - Mid Sem Exam - 50 marks
CIA III - 20 Marks - Project
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CS846E01 - COMPUTER AIDED DECISION SUPPORT SYSTEMS (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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The course will provide students with a working knowledge of topics related to Decision Support Systems design and implementation. Concepts and tools will be introduced that will be applied to different problems in Computer Science Engineering. Students will be introduced to the concepts of modelling, including simulation models and/or mathematical and empirical models, to provide for decision support. |
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Course Outcome |
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CO 1: Explain the fundamental concepts of Information system, decision system, Databases and user interfaces. CO 2: Explain model- base management systems. CO 3: Outline Decision supporting system to realize the development of decision support models, simulation models, mathematical models, verification and validation Process. CO 4: Explain recent trends related to DSS, KBS, ERP etc. CO 5: Make use of Decision support system to investigate a case study. |
Unit-1 |
Teaching Hours:9 |
Introduction to information system
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Introduction to information system analysis and design, decision support systems, Database management systems, query languages, user interfaces. | |
Unit-2 |
Teaching Hours:9 |
User interface languages
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User interface languages, usability designs and considerations, model- base management systems | |
Unit-3 |
Teaching Hours:9 |
Development of decision support models
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Development of decision support models, basic simulation models, mathematical and empirical models. Model validation and verification, algorithms for decision support, alternative analysis, Implementing EOQ models | |
Unit-4 |
Teaching Hours:9 |
Advancements in decision support systems
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Advancements in decision support systems, Knowledge-based systems, enterprise resource planning systems, manufacturing resource planning systems. | |
Unit-5 |
Teaching Hours:9 |
Application of decision support system in any engineering domain
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Application of decision support system in any engineering domain. Case study using an appropriate tool to realize the applications. and implementation. | |
Text Books And Reference Books: Vicki L Sauter, "Decision Support Systems", John Wiley & Sons, Inc. 2010 (Latest reprint) | |
Essential Reading / Recommended Reading 1. Ramez Elmasri and Shamkant Navathe, "Fundamentals of Database Systems", Addison Wesley Company. Efraim Turban, Jay Aronson, Ting- Peng Liang, and Ramesh Sharda, "Decision Support and Business Intelligence Systems", Prentice Hall Inc. | |
Evaluation Pattern CIA Marks : 50 ESE Marks: 50 | |
CS846E04 - HIGH PERFORMANCE COMPUTING (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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● To Study various computing technology architecture. ● To know Emerging trends in computing technology. To highlight the advantage of deploying computing technology. |
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Course Outcome |
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CO1: Summarize different High performance computing paradigms. CO2: Build a cluster computing system. CO3: Analyze the architecture and features of GPU systems. CO4: Develop CUDA programs. CO5: Outline the basic concepts in cloud computing. |
Unit-1 |
Teaching Hours:9 |
Overview of Parallel Computers
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Overview of Parallel Computers and high-performance computing (HPC), HPC paradigms - supercomputing, cluster computing, grid computing, cloud computing, Multi-core and GPU systems, petascale systems. Cluster computing: basics, architecture, classification, components. | |
Unit-2 |
Teaching Hours:9 |
Cluster middleware
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Cluster middleware, layers, SSI boundaries, design goals, key services of SSI, Resource management and scheduling. Cluster setup and administration (overview), security, system monitoring and system tuning. Case study – setting up of a cluster. | |
Unit-3 |
Teaching Hours:9 |
GPU programming
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GPU programming - overview of GPU architecture, CUDA, Python and CUDA, kernels, threads, blocks and grids | |
Unit-4 |
Teaching Hours:9 |
CUDA programming
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CUDA programming, streams, events, contexts and concurrency, case studies. | |
Unit-5 |
Teaching Hours:9 |
Cloud computing
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Cloud computing, basic terminologies and key features, cloud models, Public, private and hybrid clouds, architecture of cloud computing systems, Cloud data centres. | |
Text Books And Reference Books: 1. Rajkumar Buyya, High Performance Cluster Computing, Volume 1, Architecture and Systems, Pearson Education, 1999 2. Brian Tuomanen, Hands On GPU programming with Python and CUDA, Packt, 2018 | |
Essential Reading / Recommended Reading . | |
Evaluation Pattern CIA MARKS : 50 ESE MARKS : 50 | |
CS846E07 - NATURAL LANGUAGE PROCESSING (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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To provide a general introduction to natural language processing, fundamentals of parsing words in natural language, advanced feature like structures and realistic parsing methodologies with methods to handle questions with recent trends in typical natural language processing applications |
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Course Outcome |
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CO1: To understand basic concepts of NLP CO2: To analyse the classification algorithms for real time NLP problems CO3: To apply semantics and named entity concepts in NLP CO4: To apply neural network models in NLP CO5: Develop NLP models for real time applications |
Unit-1 |
Teaching Hours:9 |
Introduction
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Regular Expressions, Text Normalization, Edit Distance: Regular Expressions -Words-Corpora -Text Normalization -Minimum Edit Distance. N-gram Language Models: N-Grams -Evaluating Language Models -Generalization and Zeros -Smoothing -Kneser-Ney-Smoothing -Huge Language Models and Stupid Backoff-Advanced: Perplexity’s Relation to Entropy. | |
Unit-2 |
Teaching Hours:9 |
Naive Bayes and Sentiment Classification
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Naive Bayes Classifiers -Training the Naive Bayes Classifier -Worked example -Optimizing for Sentiment Analysis -Naive Bayes for other text classification tasks -Naive Bayes as a Language Model -Evaluation: Precision, Recall, F-measure -Test sets and Cross-validation -Statistical Significance Testing -Avoiding Harms in Classification. Logistic Regression: Classification: the sigmoid -Learning in Logistic Regression -The cross-entropy loss function -Gradient Descent -Regularization -Multinomial logistic regression -Interpreting models | |
Unit-3 |
Teaching Hours:9 |
Vector Semantics and Embeddings
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Lexical Semantics -Vector Semantics -Words and Vectors -Cosine for measuring similarity -TF-IDF: Weighing terms in the vector-Pointwise Mutual Information (PMI) -Applications of the tf-idf or PPMI vector models -Word2vec -Visualizing Embeddings -Semantic properties of embeddings -Bias and Embeddings -Evaluating Vector Models. Sequence Labeling for Parts of Speech and Named Entities: (Mostly) English Word Classes -Part-of-Speech Tagging -Named Entities and Named Entity Tagging -HMM Part-of-Speech Tagging -Conditional Random Fields (CRFs) -Evaluation of Named Entity Recognition | |
Unit-4 |
Teaching Hours:9 |
Neural Networks
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Units -The XOR problem -Feed-Forward Neural Networks -Training Neural Nets -Neural Language Models. Deep Learning Architectures for Sequence Processing: Language Models Revisited -Recurrent Neural Networks -Managing Context in RNNs: LSTMs and GRUs | |
Unit-5 |
Teaching Hours:9 |
Question Answering
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Information Retrieval -IR-based Factoid Question Answering -Entity Linking -Knowledge-based Question Answering. Chatbots & Dialogue Systems: Properties of Human Conversation -Chatbots -GUS: Simple Frame-based Dialogue Systems. Automatic Speech Recognition and Text-to-Speech: The Automatic Speech Recognition Task- Feature Extraction for ASR: Log Mel Spectrum -Speech Recognition Architecture. | |
Text Books And Reference Books: Daniel Jurafsky & James H.Martin, “ Speech and Language Processing”, Pearson Education (Singapore) Pte. Ltd., 2002. | |
Essential Reading / Recommended Reading 1. James Allen, Natural Language Understanding, Second Edition, 2003, Pearson Education. 2. Steven Bird, Ewan Klein, Edward Loper, “Natural Language Processing with Python”, O'Reilly Media; 1 edition (July 10, 2009) 3. Pushpak Bhattacharyya, “Machine Translation”, Chapman and Hall/CRC; 1 edition (January 22, 2015) 4. Matthew A Russell , “Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More”, O'Reilly Media; Second Edition edition (October 20, 2013) | |
Evaluation Pattern CIA Marks 50 ESE Marks 50 | |
CS881 - PROJECT WORK PHASE II (2020 Batch) | |
Total Teaching Hours for Semester:300 |
No of Lecture Hours/Week:20 |
Max Marks:300 |
Credits:10 |
Course Objectives/Course Description |
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Final Semester Project work is the culmination of study towards the B.Tech degree. Project work offers the students an opportunity to apply and extend the concepts learned throughout the program. Assessment will be by means of presentations, submission of a project report and a demonstration of work undertaken in front of a panel. |
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Course Outcome |
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CO1: . |
Unit-1 |
Teaching Hours:300 |
Project Work - Phase II
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Project Phase-II Project work may be assigned to a single student (with due approval from department) or to a group of students not exceeding 4 per group. Maximum Marks = 300
ESE 100 MARKS are evaluated as
PROJECT WORK GUIDELINES
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Text Books And Reference Books: NA | |
Essential Reading / Recommended Reading NA | |
Evaluation Pattern
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