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3 Semester - 2022 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
AIML331 | BASICS OF ARTIFICIAL INTELLIGENCE | Core Courses | 3 | 3 | 100 |
CS331P | DATABASE MANAGEMENT SYSTEMS | Core Courses | 5 | 4 | 100 |
CS332P | DATA STRUCTURES AND ALGORITHMS | Core Courses | 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 |
AIML451 | PYTHON FOR AI AND ML | - | 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 |
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 |
AIML532 | INTRODUCTION TO MACHINE LEARNING | Core Courses | 3 | 3 | 100 |
CS531P | COMPUTER NETWORKS | Core Courses | 5 | 4 | 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 |
CSHO533CSP | CYBER FORENSICS AND MALWARE DETECTION | Minors and Honours | 5 | 4 | 100 |
CSHO533DAP | BIG DATA SECURITY ANALYTICS | 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 |
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 |
AIML633P | DIGITAL IMAGE PROCESSING | - | 5 | 4 | 100 |
AIML634 | SOFT COMPUTING | - | 3 | 3 | 100 |
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 |
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 |
CS642E07 | DATA WAREHOUSING AND DATA MINING | - | 3 | 3 | 100 |
CS681 | SERVICE LEARNING | - | 2 | 2 | 50 |
CSHO681CSP | CS PROJECT/CERTIFICATE COURSES | - | 5 | 4 | 100 |
CSHO681DAP | DA PROJECT/CERTIFICATE COURSES | - | 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 |
AIML735P | NEURAL NETWORK | Core Courses | 3 | 3 | 100 |
AIML736 | PATTERN RECOGNITION | Core Courses | 3 | 3 | 100 |
AIML782 | PROJECT WORK PHASE I | Project | 8 | 4 | 100 |
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 |
CS743E06 | WEB SERVICES AND SERVICE ORIENTED ARCHITECTURE | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS743E08 | SOFTWARE PROJECT MANAGEMENT | Discipline Specific Elective Courses | 3 | 3 | 100 |
CS781 | INTERNSHIP - II | Project | 2 | 1 | 50 |
CSHO731CSP | INTRUSION DETECTION AND INCIDENT RESPONSE | Minors and Honours | 5 | 4 | 100 |
CSHO731DAP | WEB ANALYTICS | Minors and Honours | 5 | 4 | 100 |
CSHO781CSP | CS PROJECT/CERTIFICATE COURSES | Minors and Honours | 5 | 4 | 100 |
CSHO781DAP | DA PROJECT / CERTIFICATE COURSES | Minors and Honours | 5 | 4 | 100 |
MA736OE3 | NUMERICAL SOLUTIONS OF DIFFERENTIAL EQUATIONS | Interdisciplinary Elective Courses | 3 | 3 | 100 |
ME761E03 | BASIC AUTOMOBILE ENGINEERING | Interdisciplinary Elective Courses | 3 | 3 | 100 |
ME761E04 | SMART MATRIALS AND APPLICATIONS | Interdisciplinary Elective Courses | 3 | 3 | 100 |
ME761E05 | BASIC AEROSPACE ENGINEERING | 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 |
AIML844E01 | COMPUTER AIDED DECISION SUPPORT SYSTEMS | - | 3 | 3 | 100 |
AIML844E03 | HIGH PERFORMANCE COMPUTING | - | 3 | 3 | 100 |
AIML844E04 | NATURAL LANGUAGE PROCESSING | - | 3 | 3 | 100 |
AIML881 | PROJECT WORK PHASE II | - | 20 | 10 | 300 |
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Computer Science and Engineering with spacilization( Artificial Intelligence and Machine Learning) is a 4 year, 8 semester Undergraduate program aimed at studying, designing, developing, implementing, support and management of computer-based information systems. Students under this course concentrate on the concepts of Artificial Intelligence and Machine learning roles on both software and hardware areas. It provides advanced studies in Information Systems Design, Communication Systems and Networking, Foundations of Computing Systems, and Internet and Web-based Technologies. Students have to take up electives from a wide choice of subjects, such as Embedded Low Power Systems, Object Oriented Systems, Information and System Security and Software Reliability.These course emphases on to develop the necessary skills for the students to sustain in today’s industrial expectation, in pursuit of excellence by keeping high personal and professional values and ethics. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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: Software Architecture: Apply the concepts of software engineering to Design and Develop software applicationsPSO2: Resource Management: Utilize the knowledge of Artificial Intelligence & Machine Learning to develop AI based solutions for the real-world problems PSO3: Reflections through Service: Analyze Social Relevant Problems and Design Software /IT based solutions through Service Learning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Examination And Assesments | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
● Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks) |
AIML331 - BASICS OF ARTIFICIAL INTELLIGENCE (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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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: Identify the fundamental knowledge of Intelligent agents, searching strategies and syntax and semantics of first order logic. CO2: Discover the complex problem-solving agents, constraint satisfaction problems and optimal decisions in game. CO3: Inspect the knowledge engineering in first order logic, knowledge representation and chaining mechanisms, knowledge in learning and different forms of learning. CO4: Determine and build planning strategies, Communication and analysis of grammar and its interpretation. CO5: Asses a system that utilize artificial intelligence to a complicated task with limited resources in the form of time and computations. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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] |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
VCSE111 - PCAP PROGRAMMING ESSENTIALS IN PYTHON (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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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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
AIML451 - PYTHON FOR AI AND ML (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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Course Outcome |
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CO1: Summarize the fundamentals of Python Programming Constructs for problem solving. CO2: Demonstrate the use of control flow and Functions for solving problems. CO3: Utilize List, Modules and Packages to develop solutions for real life problems. CO4: Model solutions of real-life use cases using Files, Modules and Packages through data processing and analysis. CO5: Analyse, visualize and perform predictive modelling of data using Python. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
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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 |
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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. |
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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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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) |
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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 |
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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} |
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AIML532 - INTRODUCTION TO MACHINE LEARNING (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 objectives: • To understand the need for machine learning • To discover supervised and unsupervised learning paradigm of machine learning • To learn various machine learning techniques • To design suitable machine learning algorithms for solving problems |
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Course Outcome |
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CO1: Describe various supervised learning methods. CO2: Discuss various unsupervised learning methods. CO3: Explain the basics of neural networks and back propagation algorithm for problem solving. CO 4: Use the concept of Bayesian theory to machine learning. CO5: Understand various learning techniques in the Machine Learning |
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CS531P - COMPUTER NETWORKS (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 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. |
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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. |
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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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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: . |
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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. |
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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 |
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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: . |
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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 |
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To analyze about best possible solutions for different vulnerabilities that are exploited for hacking |
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Course Outcome |
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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 |
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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 |
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To provide the fundamental techniques and principles of security model in Big Data. |
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Course Outcome |
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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 |
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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. |
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Course Outcome |
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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. |
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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 |
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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. |
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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 |
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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. |
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Course Outcome |
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CO-1: Understand the architecture, programming and interfacing principles of ATMEGA32 AVR microcontroller and Rasberry P |
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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 |
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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 |
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Course Outcome |
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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. |
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EEOE531 - HYBRID ELECTRIC VEHICLES (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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This course introduces the fundamental concepts, principles, analysis and design of hybrid and electric vehicles. |
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Course Outcome |
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· 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. |
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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 |
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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. |
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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} |
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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 |
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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
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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: . |
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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. |
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Course Outcome |
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CO1: . |
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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 |
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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. |
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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. |
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AIML633P - DIGITAL IMAGE PROCESSING (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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• The students will learn the fundamental concepts of Image Processing. • The students will learn image enhancement techniques in spatial & frequency domain • The students will learn the restoration & compression models. • Help the students to segmentation and representation techniques for the region of interests. • The students will learn the how to recognize objects using pattern recognition techniques. |
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Course Outcome |
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CO1: Identify the fundamental concepts of image formation and image transformations. CO2: Interpret histogram and their use to enhance quality of images based on matching and specification techniques. CO3: Demonstrate the use of degradation function for distorted images and compare compression techniques. CO4: Evaluate Morphological processing for image representation. CO5:Utilize descriptors and patterns to describe an image for object recognition. |
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AIML634 - SOFT COMPUTING (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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The course will introduce the basic concepts in Soft computing, give an overview of Soft Computing approaches VIZ Fuzzy Logic, Genetic algorithms, Simulated Annealing and Artificial Neural Networks and familiarize with soft computing solutions to problems. |
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Course Outcome |
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CO1: Solve Fuzzy set, relation, reasoning and rule-based problems. CO2: Understand the basic concept of Optimization Algorithms. Differentiate traditional and nature inspired algorithms. CO3: Understand the basics of different nature inspired algorithms and their working. CO4: Experiment with the different nature inspired algorithms. CO5: Solve complex real-world problems with use of nature inspired algorithms. |
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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 |
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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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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
BTGE635 - INTELLECTUAL PROPERTY RIGHTS (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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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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
BTGE651 - DATA ANALYTICS THROUGH SPSS (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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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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
BTGE652 - DIGITAL MARKETING (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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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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
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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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
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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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
BTGE658 - DESIGN THINKING (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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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) |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
CS642E07 - DATA WAREHOUSING AND DATA MINING (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 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: . |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 . |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
AIML735P - NEURAL NETWORK (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 offers project-based learning. The students would learn to observe, analyze the need of the neighboring society . They will propose technically feasible solutions and develop the solutions for the identified community, through which they develop communication skill, team work, ethics and life long learning apart from technical knowledge.
Course Objectives are:
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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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
AIML736 - PATTERN RECOGNITION (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 Outcome |
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CO1: Explain the basic principles of pattern recognition systems.
CO2: Examine the features and applications of Bayesian decision theory.
CO3: Apply the maximum-likelihood and Bayesian parameter estimation for designing classifiers.
CO4: Explain Non-parametric Techniques for classification problems. CO5: Examine unsupervised learning concepts for the design of clustering algorithms. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
AIML782 - PROJECT WORK PHASE I (2020 Batch) | |
Total Teaching Hours for Semester:120 |
No of Lecture Hours/Week:8 |
Max Marks:100 |
Credits:4 |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
CEOE732 - AIR POLLUTION AND CONTROL (2020 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:03 |
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 |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
CEOE733 - GIS AND REMOTE SENSING TECHNIQUES AND APPLICATIONS (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 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. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
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 |
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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. |
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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 |
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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. |
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Course Outcome |
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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. |
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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 |
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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. |
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Course Outcome |
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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. |
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CS743E06 - WEB SERVICES AND SERVICE ORIENTED ARCHITECTURE (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 introduces service-oriented architectures and their basic principles. Also providing basic and advanced concepts of web services such as protocols, SOAP, RESTful, and building enterprise solutions. |
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Course Outcome |
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CO1: Demonstrate the applicability of SOA Concepts and the goals of the REST Architectural Style. CO2: Apply requirements towards the creation of a REST web service , Design Principles and Constraints. CO3: Analyze Service Modeling, Service Contract in SOA and Service Oriented design With REST. CO4: Develop RESTful services as part of service-oriented solutions in conjunction with service-oriented architecture (SOA). CO5: Design solutions for web services that follow the REST architectural style. |
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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 |
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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. |
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Course Outcome |
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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. |
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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. |
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CSHO731CSP - INTRUSION DETECTION AND INCIDENT RESPONSE (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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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. |
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Course Outcome |
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CO1: Explain the evolution from design protection to detection of intrusions. CO2: Summarize the various intrusion detection system and its architectural models CO3: Identify the incident response when a computer intrusion occurs. CO4: Analyze the parameters needed to detect intrusions. CO5: Evaluate the best practices that comprise intrusions with incident responses. |
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CSHO731DAP - WEB ANALYTICS (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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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. |
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CSHO781CSP - CS 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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• 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 problems |
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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 |
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MA736OE3 - NUMERICAL SOLUTIONS OF DIFFERENTIAL EQUATIONS (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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Many physical laws are couched in terms of rate of change of one/two or more independent variables, most of the engineering problems are characterized in the form of either nonlinear ordinary differential equations or partial differential equations. The methods introduced in the solution of ordinary differential equations and partial differential equations will be useful in attempting any engineering problem. |
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Course Outcome |
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CO-1: Operate multistep numerical techniques to solve first and second order ordinary differential equations. {L3} {PO1, PO2, PO3, PO5, PO6, PO8, PO9, PO12} CO-2: Construct finite difference approximations to solve boundary value problems. {L3} {PO1, PO2, PO3, PO4, PO9, PO12} CO-3: Develop finite difference schemes for Parabolic equation. {L3} {PO1, PO2, PO4, PO9, PO12} CO-4: Apply finite difference method to solve boundary value problems of hyperbolic and elliptic differential equations {L3} {PO1, PO2, PO6, PO7, PO9, PO10, PO11, PO12} CO-5: Evaluating the Boundary value problems of Linear and Non-Linear Differential Equations using Open Software's. |
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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. |
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ME761E04 - SMART MATRIALS AND APPLICATIONS (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 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} |
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ME761E05 - BASIC AEROSPACE 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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Course Outcome |
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Upon completion of this course, the students will be able to CO1: To explain flow regimes (viscous/non-viscous; compressible/incompressible aerodynamics) and to estimate viscous and thermal effects.(L2) |
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NCCOE2 - NCC2 (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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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) |
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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}
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AIML844E01 - 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. |
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AIML844E03 - 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. |
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AIML844E04 - 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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AIML881 - 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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