CHRIST (Deemed to University), Bangalore

DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

School of Business and Management

Syllabus for
Bachelor of Technology (Computer Science and Engineering-Data Science)
Academic Year  (2023)

 
3 Semester - 2022 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
CS331P DATABASE MANAGEMENT SYSTEMS Core Courses 5 4 100
CS332P DATA STRUCTURES AND ALGORITHMS Core Courses 5 4 100
CSHO331AIP STATISTICAL FOUNDATION FOR ARTIFICIAL INTELLIGENCE Minors and Honours 5 4 100
CSHO331CSP PROBABILITY AND RANDOM PROCESS Minors and Honours 5 4 100
CY321 CYBER SECURITY Skill Enhancement Courses 2 0 0
DS331P STATISTICAL FOUNDATION FOR BIG DATA Core Courses 5 4 100
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
CS432P OPERATING SYSTEMS Core Courses 5 4 100
CS433P PROGRAMMING PARADIGM Core Courses 5 4 100
CS434 FORMAL LANGUAGE AND AUTOMATA THEORY Core Courses 3 3 100
CS435P COMPUTER ORGANIZATION AND ARCHITECTURE Core Courses 5 4 100
CSHO432AIP ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Minors and Honours 5 4 100
CSHO432CSP MOBILE AND NETWORK BASED ETHICAL HACKING Minors and Honours 5 4 100
DS451 PYTHON FOR DATA SCIENCE Core Courses 2 1 100
EVS421 ENVIRONMENTAL SCIENCE Skill Enhancement Courses 2 0 0
HS422 PROFESSIONAL ETHICS Core Courses 2 2 50
MA431 PROBABILITY AND QUEUING THEORY Core Courses 3 3 100
5 Semester - 2021 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
CS531P COMPUTER NETWORKS Core Courses 5 4 100
CS532 INTRODUCTION TO ARTIFICIAL INTELLIGENCE Core Courses 3 3 100
CS533P DESIGN AND ANALYSIS OF ALGORITHMS Core Courses 5 4 100
CS541E01 COMPUTER GRAPHICS WITH OPEN GL Discipline Specific Elective Courses 3 3 100
CS541E02 INTERNET AND WEB PROGRAMMING Discipline Specific Elective Courses 3 3 100
CS541E04 CRYPTOGRAPHY AND NETWORK SECURITY Discipline Specific Elective Courses 3 3 100
CS581 INTERNSHIP - I Project 2 1 50
CSHO533AIP ROBOTICS AND PROCESS AUTOMATION Minors and Honours 5 4 100
CSHO533CSP CYBER FORENSICS AND MALWARE DETECTION Minors and Honours 5 4 100
CSHO534AIP COMPUTER VISION Minors and Honours 5 4 100
CSHO534CSP INTRUSION DETECTION AND INCIDENT RESPONSE Minors and Honours 5 4 100
ECOE5601 EMBEDDED BOARDS FOR IOT APPLICATIONS Interdisciplinary Elective Courses 3 3 100
ECOE5602 FUNDAMENTALS OF IMAGE PROCESSING Interdisciplinary Elective Courses 3 3 100
ECOE5603 OBSERVING EARTH FROM SPACE Interdisciplinary Elective Courses 3 3 100
EEOE531 HYBRID ELECTRIC VEHICLES Interdisciplinary Elective Courses 4 3 100
EEOE532 ROBOTICS AND AUTOMATION Interdisciplinary Elective Courses 4 3 100
EEOE533 SMART GRIDS Interdisciplinary Elective Courses 3 3 100
HS521 PROJECT MANAGEMENT AND FINANCE Discipline Specific Elective Courses 3 3 100
IC521 CONSTITUTION OF INDIA Skill Enhancement Courses 2 0 50
IT541E01 UNIX AND SHELL PROGRAMMING Discipline Specific Elective Courses 3 3 100
NCCOE1 NCC1 Interdisciplinary Elective Courses 3 3 100
VCSE514 CCNA: INTRODUCTION TO NETWORKS (ITN) - 4 0 100
VCSE516 FULL STACK WEB DEVELOPMENT - 4 0 100
6 Semester - 2021 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
BTGE631 CORPORATE SOCIAL RESPONSIBILITY Generic Elective Courses 2 2 100
BTGE632 DIGITAL MEDIA Generic Elective Courses 2 2 100
BTGE633 FUNCTIONAL ENGLISH Generic Elective Courses 2 2 100
BTGE634 GERMAN Generic Elective Courses 2 2 100
BTGE635 INTELLECTUAL PROPERTY RIGHTS Generic Elective Courses 2 2 100
BTGE636 INTRODUCTION TO AVIATION Generic Elective Courses 2 2 100
BTGE637 PROFESSIONAL PSYCHOLOGY Generic Elective Courses 2 2 100
BTGE651 DATA ANALYTICS THROUGH SPSS Generic Elective Courses 2 2 100
BTGE652 DIGITAL MARKETING Generic Elective Courses 2 2 100
BTGE653 DIGITAL WRITING Generic Elective Courses 2 2 100
BTGE654 PHOTOGRAPHY Generic Elective Courses 2 2 100
BTGE655 ACTING COURSE Generic Elective Courses 2 2 100
BTGE656 CREATIVITY AND INNOVATION Generic Elective Courses 2 2 100
BTGE657 PAINTING AND SKETCHING Generic Elective Courses 2 2 100
BTGE658 DESIGN THINKING Generic Elective Courses 2 2 100
CS632P COMPILER DESIGN Core Courses 5 4 100
CS642E01 MOBILE APPLICATION DEVELOPMENT Discipline Specific Elective Courses 3 3 100
CS642E03 ADVANCED DATABASES Discipline Specific Elective Courses 3 3 100
CS642E06 SYSTEM SOFTWARE Discipline Specific Elective Courses 3 3 100
CS642E07 DATA WAREHOUSING AND DATA MINING Discipline Specific Elective Courses 3 3 100
CS681 SERVICE LEARNING Project 2 2 50
CSHO681AIP AI PROJECT /CERTIFICATE COURSES Minors and Honours 5 4 100
CSHO681CSP CS PROJECT/CERTIFICATE COURSES Minors and Honours 5 4 100
DS634 BUSINESS INTELLIGENCE Core Courses 3 3 100
DS635P BIG DATA ANALYTICS Core Courses 3 3 100
IT642E02 FOUNDATIONS TO BLOCKCHAIN TECHNOLOGY Discipline Specific Elective Courses 3 3 100
MIIMBA634 DATA ANALYSIS FOR MANAGERS Minors and Honours 3 4 100
7 Semester - 2020 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
CEOE731 SUSTAINABLE AND GREEN TECHNOLOGY Interdisciplinary Elective Courses 3 3 100
CEOE732 AIR POLLUTION AND CONTROL Interdisciplinary Elective Courses 3 03 100
CEOE733 GIS AND REMOTE SENSING TECHNIQUES AND APPLICATIONS Interdisciplinary Elective Courses 3 3 100
CS743E02 TCP/IP DESIGN AND IMPLEMENTATION Discipline Specific Elective Courses 3 3 100
CS743E03 SIMULATION AND MODELING Discipline Specific Elective Courses 3 3 100
CS743E04 SOFTWARE PROCESS AND PROJECT MANAGEMENT Discipline Specific Elective Courses 3 3 100
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
CS744E01 INFORMATION STORAGE AND MANAGEMENT Discipline Specific Elective Courses 3 3 100
CS744E02 DATA BASE ADMINISTRATION Discipline Specific Elective Courses 3 3 100
CS744E03 NETWORK STORAGE TECHNOLOGIES Discipline Specific Elective Courses 3 3 100
CS744E04 NETWORK ADMINISTRATION Discipline Specific Elective Courses 3 3 100
CS744E05 RESEARCH METHODOLOGY Discipline Specific Elective Courses 3 3 100
CS781 INTERNSHIP - II Project 2 1 50
CSHO731AIP COMPUTER VISION Minors and Honours 5 4 100
CSHO781AIP AI PROJECT/ MOOC COURSE/ CERTIFIED COURSE Minors and Honours 5 4 100
DS737P WEB ANALYTICS Core Courses 5 4 100
DS782 PROJECT WORK PHASE I Project 8 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
8 Semester - 2020 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
DS845E01 COMPUTER AIDED DECISION SUPPORT SYSTEMS Discipline Specific Elective Courses 3 3 100
DS845E04 HIGH PERFORMANCE COMPUTING Discipline Specific Elective Courses 3 3 100
DS845E07 NATURAL LANGUAGE PROCESSING Discipline Specific Elective Courses 3 3 100
DS881 PROJECT WORK PHASE II Project 20 10 300
    

    

Introduction to Program:

  Computer Science and Engineering with specilization(Data Science) 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 role of Data Sceince in 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 Data Architecture: Use modern tools and associated skills in the areas of computer science engineering, technology and data sciences

PSO2: Data Exploration and Analytics: Ability to implement data science techniques in drawing meaningful solutions through data analytics which aid in successful career and entrepreneurship

PSO3: Knowledge representation for real-world problems: Understand, analyze and develop essential proficiency in the concepts related to statistical and computational principles of data science in solving practical problems

Assesment Pattern

COURSES WITH THEORY AND PRACTICAL

 

Component

Assessed for

Minimum marks

to pass

Maximum

marks

1

Theory CIA

30

-

30

2

Theory ESE

30

12

30

3

Practical CIA

35

14

35

4

Attendance

05

-

05

4

Aggregate

100

40

100

 

DETAIL OF MARK FOR COURSES WITH THOERY AND PRACTICAL

THEORY

PRACTICAL

 

Component

Assessed for

Scaled down to

Minimum marks topass

Maximum marks

Component

Assessed for

Scaled down to

Minimum marks to pass

Maximum marks

1

CIA-1

20

10

-

10

Overall CIA

50

35

14

35

2

CIA-2

50

10

-

10

 

 

 

3

CIA-3

20

10

-

10

 

 

 

4

Attendance

05

05

-

05

Attendance

NA

NA

-

-

5

ESE

100

30

12

30

ESE

NA

NA

-

-

 

 

TOTAL

65

-

65

TOTAL

 

35

14

35

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)

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

 

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

Course Outcome

C01: Apply the Conepts of Entity-Relationship (E-R) model for the given application.

CO2: Apply Normalization principles to create and maniplulate relational databases

CO3: Apply the concepts of Non-Relational Models

CO4: Examine different file organization concepts for data storage in Relational databases

CO5: Apply the transaction management principles on relational databases

Unit-1
Teaching Hours:9
INTRODUCTION AND CONCEPTUAL MODELING
 

Introduction to File and Database systems- Database system structure – Data Models – Introduction to Network and Hierarchical Models – ER model – Relational Model – Relational Algebra.

Unit-2
Teaching Hours:9
RELATIONAL MODEL
 

SQL – Data definition- Queries in SQL- Updates- Views – Integrity and Security – Relational Database design – Functional dependencies and Normalization for Relational Databases (up to BCNF).

Unit-3
Teaching Hours:9
NON RELATIONAL MODEL
 

Introduction to NOSQL Systems ,The CAP Theorem, Document-Based NOSQL Systems and MongoDB, NOSQL Key-Value Stores, Column-Based or Wide Column NOSQL Systems, NOSQL Graph Databases and Neo4j 

Unit-4
Teaching Hours:9
DATA STORAGE AND QUERY PROCESSING
 

Record storage and Primary file organization- Secondary storage Devices- Operations on FilesHeap File- Sorted Files- Hashing Techniques – Index Structure for files –Different types of Indexes- B-Tree - B+ Tree – Query Processing.

Unit-5
Teaching Hours:9
TRANSACTION MANAGEMENT
 

Transaction management -Transaction Processing – Introduction- Need for Concurrency control- Desirable properties of Transaction- Schedule and Recoverability- Serializability and Schedules – Concurrency Control – Types of Locks- Two Phases locking- Deadlock- Time stamp based concurrency control – Recovery Techniques – Concepts- Immediate Update- Deferred Update - Shadow Paging.

Text Books And Reference Books:

 Abraham Silberschatz, Henry F. Korth and S. Sudarshan- “Database System Concepts”, Seventh Edition, McGraw-Hill, 2021

Essential Reading / Recommended Reading

Andreas Meier · Michael Kaufmann "SQL & NoSQL Databases", Springer -2019

Raghu Ramakrishnan, “Database Management System”, Tata McGraw-Hill Publishing Company, 2003

Online Resources: W1.http://db-book.com/db6/slide-dir

Evaluation Pattern

CIA:70/100

ESE:30/100

CS332P - DATA STRUCTURES AND ALGORITHMS (2022 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

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.

Course Outcome

CO1: Implement various ADT and Calculate the complexity of the algorithm

CO2: Experiment with various operations on Linear Data structures

CO3: Experiment with various Non- Linear Data structures and Hashing techniques

CO4: Compare different sorting techniques with respect to time complexity

CO5: Make use of graph algorithms in various applications of graph traversal, shortest path and sorting techniques.

Unit-1
Teaching Hours:11
INTRODUCTION and STACK ADT
 

Definition- Classification of data structures: primitive and non-primitive- Operations on data structures- Algorithm Analysis: Introduction. The Stack ADT: Definition, Array representation of stack, Operations on stack: Infix, prefix and postfix notations Conversion of an arithmetic Expression from Infix to postfix. Applications of stacks.

Unit-2
Teaching Hours:14
LISTS AND QUEUES
 

The Queue ADT: Definition, Array representation of queue, Types of queues: Simple queue, circular queue, double ended queue (de-queue) priority queue, operations on all types of Queues. The List ADT: singly linked list implementation, insertion, deletion and searching operations on linear list, circular linked list implementation, Double linked list implementation, insertion, deletion and searching operations. Applications of linked lists.

Unit-3
Teaching Hours:13
TREES
 

Preliminaries – Binary Trees – The Search Tree ADT – Binary Search Trees – AVL Trees – Tree Traversals – Hashing – General Idea – Hash Function – Separate Chaining – Open Addressing –Linear Probing – Priority Queues (Heaps) – Model – Simple implementations – Binary Heap

Unit-4
Teaching Hours:20
SORTING
 

Preliminaries – Insertion Sort, Selection sort – Shell sort – Heap sort – Merge sort – Quicksort – External Sorting

Unit-5
Teaching Hours:14
GRAPHS
 

Introduction to Graphs, Definitions –DFS, BFS,  Minimum Spanning Tree – Prim’s and Kruskal's Algorithm.  Single-Source Shortest Paths – Bellman-Ford algorithm and Dijkstra’s Algorithm – Applications of Graphs

Text Books And Reference Books:

T1. Mark Allen Weiss, “Data Structures and Algorithm Analysis in C”, 3rd Edition, Pearson Education 2013.

Essential Reading / Recommended Reading

R1. Fundamentals of data structure in C by Ellis Horowitz, Sarataj Shani 3rd edition, Galgotia book source PVT,2010.

R2. Classic Data Structures , Debasis Samanta ,2nd Edition, PHI Learning PVT,2011

Evaluation Pattern

CIA-70/100

ESE-30/100

CSHO331AIP - STATISTICAL FOUNDATION FOR ARTIFICIAL INTELLIGENCE (2022 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

      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

Course Outcome

CO 1: Demonstrate concepts associated to Statistical Analytics and Data manipulation

CO 2: Experiment with Data Visualization, Statistical Graphics and Statistical Inference.

CO 3: Solve Problems related to Statistical Learning and Data Analytics

CO 4: Make use of Supervised learning to solve real life problems

CO 5: Apply Supervised, Unsupervised and Ensemble learning to solve real life problems.

Unit-1
Teaching Hours:9
STATISTICAL ANALYTICS AND DATA MANIPULATION
 

Knowledge discovery: finding structure in data, Data quality versus data quantity, Statistical modeling versus statistical description. Data types, Data summarization, Means, medians, and central tendency, Summarizing variation, Summarizing (bivariate) correlation, Data diagnostics and data transformation, Outlier analysis, Entropy, Data transformation Simple smoothing techniques, Binning, Moving averages, Exponential smoothing. Introduction to SPSS (IBM’s) statistical tool.

Unit-2
Teaching Hours:9
TECHNIQUES FOR SUPERVISED AND UNSUPERVISED LEARNING
 

The simple linear model, Multiple inferences and simultaneous confidence bands, Regression diagnostics, Weighted least squares (WLS) regression, Correlation analysis. Unsupervised versus supervised learning, Principal component analysis, Principal components, Implementing a PCA, Exploratory factor analysis.

Unit-3
Teaching Hours:9
NEURAL NETWORKS
 

Projection Pursuit Regression, Neural Networks, Fitting Neural Network, Some Issues in Training Neural Networks, Bayesian Neural Nets, 0 Computational Considerations.

Unit-4
Teaching Hours:9
SUPPORT VECTOR MACHINES AND FLEXIBLE DISCRIMINANTS
 

Introduction, The Support Vector Classifier, Support Vector Machines and Kernels, Generalizing Linear Discriminant Analysis, Flexible Discriminant Analysis, Penalized Discriminant Analysis, Mixture Discriminant Analysis

Unit-5
Teaching Hours:9
RANDOM FORESTS AND ENSEMBLE LEARNING
 

Definition of Random Forests, Details of Random Forests- Out of Bag Samples, Variable Importance, Proximity Plots; Analysis of Random Forests; Ensemble Learning, Boosting and Regularization Paths, Learning a Good Ensemble, Rule Ensembles.

Text Books And Reference Books:

T1. Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media, 2017.

T2. Russell, Stuart J., and Peter Norvig. Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited,, 2016.

Essential Reading / Recommended Reading

R1. Ghahramani, Zoubin. "Probabilistic Machine Learning and Artificial Intelligence." Nature521.7553 (2015): 452.

R2. Ian Goodfellow and Yoshua Bengio and Aaron Courville,” Deep Learning ”, MIT Press, March 2018.

R3. Wu, James, and Stephen Coggeshall. Foundations of predictive analytics. Chapman and Hall/CRC, 2012.

R4. Marcoulides, George A., and Scott L. Hershberger. Multivariate statistical methods: A first course. Psychology Press, 2014.

R5. Morgan, George A., et al. IBM SPSS for introductory statistics: Use and interpretation. Routledge, 2012

Evaluation Pattern

CIA 70 marks

ESE 30 marks

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

 

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.

Course Outcome

CO1: To define pattern searching algorithms for different applications

CO2: To classify vulnerability of subsystem based on the information gathered from different resources

CO3: To estimate different optimized process and models

CO4: To provide means to find the similarities between the applications and vulnerabilities of the sub-system/system

CO5: To analyze about best possible patterns to cluster the possible solutions for different vulnerabilities

Unit-1
Teaching Hours:9
Unit 1
 

Probability Fundamentals, Bayes’ rule, Markov chains and application to pattern search algorithms, Classical statistical inference, Bayesian statistical inference, Regression techniques

Unit-2
Teaching Hours:9
Unit 2
 

Information coding, Pseudorandom number generators, discrete random variables, special distributions and mixed random variables, link and rank analysis , probability bounds, limiting theorem and convergence 

Unit-3
Teaching Hours:9
unit 3
 

Risk M Basics of statistical learning: models, regression, curse of dimensionality, overfitting, etc. Optimization and convexity, Gradient descent, Newton’s method 

Unit-4
Teaching Hours:9
unit 4
 

Classification and similarity analysis, linear discriminative analysis, regression analysis, iterative permutation analysis, Support vector machines, nearest neighbor and application of entropy

Unit-5
Teaching Hours:9
unit 5
 

Clustering algorithms, graph analysis, pattern detection, Knowledge driven system design, learning with errors, Basics of neural networks

Text Books And Reference Books:

T1. Gnedenko, Boris V. Theory of probability. Routledge, 2018.

T2. Beichelt, Frank. Applied Probability and Stochastic Processes. Chapman and Hall/CRC, 2016.

T3. Li, X. Rong. Probability, random signals, and statistics. CRC press, 2017

Essential Reading / Recommended Reading

R1. Grimmett, Geoffrey, Geoffrey R. Grimmett, and David Stirzaker. Probability and random processes. Oxford university press, 2001.

R2. Papoulis, Athanasios, and S. Unnikrishna Pillai. Probability, random variables, and stochastic processes. Tata McGraw-Hill Education, 2002.

R3. Rozanov, Yu. Probability theory, random processes and mathematical statistics. Vol. 344. Springer Science & Business Media, 2012.

Evaluation Pattern

CIA 70 marks

ESE 30 marks

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

 

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

Course Outcome

CO1: Describe the basic security fundamentals and cyber laws and legalities

CO2: Describe various cyber security vulnerabilities and threats such as virus, worms, online attacks, Dos and others.

CO3: Explain the regulations and acts to prevent cyber-attacks such as Risk assessment and security policy management.

CO4: Explain various vulnerability assessment and penetration testing tools.

CO5: Explain various protection methods to safeguard from cyber-attacks using technologies like cryptography and Intrusion prevention systems.

Unit-1
Teaching Hours:6
UNIT 1
 

Security Fundamentals-4 As Architecture Authentication Authorization Accountability, Social Media, Social Networking and Cyber Security.Cyber Laws, IT Act 2000-IT Act 2008-Laws for Cyber-Security, Comprehensive National Cyber-Security Initiative CNCI – Legalities

Unit-2
Teaching Hours:6
UNIT 2
 

Cyber Attack and Cyber Services Computer Virus – Computer Worms – Trojan horse.Vulnerabilities -  Phishing -  Online Attacks – Pharming - Phoarging  –  Cyber Attacks  -  Cyber Threats -  Zombie- stuxnet - Denial of Service Vulnerabilities  - Server Hardening-TCP/IP attack-SYN Flood

Unit-3
Teaching Hours:6
UNIT 3
 

Cyber Security Management Risk Management and Assessment - Risk Management Process - Threat Determination Process -Risk Assessment - Risk Management Lifecycle.Security Policy Management - Security Policies - Coverage Matrix Business Continuity Planning - DisasterTypes  -  Disaster Recovery Plan - Business Continuity Planning Process

Unit-4
Teaching Hours:6
UNIT 4
 

Vulnerability - Assessment and Tools: Vulnerability Testing - Penetration Testing Black box- white box.Architectural Integration:  Security Zones - Devicesviz Routers, Firewalls, DMZ. Configuration Management - Certification and Accreditation for Cyber-Security.

Unit-5
Teaching Hours:6
UNIT 5
 

Authentication and Cryptography: Authentication - Cryptosystems - Certificate Services, Securing Communications:  Securing Services -  Transport  –  Wireless  -  Steganography and NTFS Data Streams. Intrusion Detection and Prevention Systems:   Intrusion -  Defense in Depth  -  IDS/IPS  -IDS/IPS Weakness and Forensic AnalysisCyber Evolution: Cyber Organization – Cyber Future

Text Books And Reference Books:

R1. Matt Bishop, “Introduction to Computer Security”, Pearson, 6th impression, ISBN: 978-81-7758-425-7.

R2. Thomas R, Justin Peltier, John, “Information Security Fundamentals”, Auerbach Publications.

R3. AtulKahate, “Cryptography and Network Security”,  2nd Edition, Tata McGrawHill.2003

R4. Nina Godbole, SunitBelapure, “Cyber Security”, Wiley India 1st Edition 2011

R5. Jennifer L. Bayuk and Jason Healey and Paul Rohmeyer and Marcus Sachs, “Cyber Security Policy Guidebook”, Wiley; 1 edition , 2012

R6. Dan Shoemaker and Wm. Arthur Conklin, “Cyber security: The Essential Body Of Knowledge”,   Delmar Cengage Learning; 1 edition, 2011

R7. Stallings, “Cryptography & Network Security - Principles & Practice”, Prentice Hall, 6th Edition 2014

Essential Reading / Recommended Reading

NIL

Evaluation Pattern

Only CIA will be conducted as per the University norms. No ESE

Maximum Marks : 50

DS331P - STATISTICAL FOUNDATION FOR BIG DATA (2022 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Course objectives: 

  • Relate concepts of statistics, data analytics and probability functions
  • Illustrate scenarios in random process and standard distributions
  • Examine various graphical illustrations with appropriate statistical parameters
  • Choose techniques of supervised and unsupervised learning mechanisms for solving related problems
  • Interpret the correlation analysis and associated aspects concerning to a case study

Course Outcome

CO 1: Understand and explain concepts associated to basics in statistics and data analytics

CO 2: Solve problems connected to random process and standard distributions

CO 3: Experiment and visualize defined data sets and their different graphical illustrations

CO 4: Infer details of supervised and unsupervised learning mechanisms

CO 5: Construct correlation analysis

Unit-1
Teaching Hours:14
Introduction to Statistical Analysis and Data Science
 

Data Science Traits, Concepts of Big data need for data analytics, Knowledge discovery: finding structure in data, Data quality versus data quantity, Statistical modeling versus statistical description, Data Visualization, measuring Correlation Co-efficient.  

Unit-2
Teaching Hours:16
Probability Distribution Functions
 

Concepts in Probability, Total Probability Theorem, Bayes Theorem, Random Variables, Means, variances, and expected values; Standard Distributions- Binomial, Poisson, Geometric, Uniform, Exponential and Normal (Gaussian) distribution, Central Limit Theorem. 

Unit-3
Teaching Hours:15
Data manipulation
 

Data types, Data summarization, Means, medians, and central tendency, Summarizing variation, Summarizing (bivariate) correlation, Data diagnostics and data transformation, Outlier analysis, Entropy, Data transformation Simple smoothing techniques, Binning, Moving averages, Exponential smoothing. Introduction to SPSS (IBM’s) statistical tool. 

Unit-4
Teaching Hours:16
Data visualization and statistical graphics
 

Univariate visualization, Strip charts and dot plots, Boxplots, Stem-and-leaf plots, Histograms, Quantile plots, Bivariate and multivariate visualization, Pie charts and bar charts, Multiple boxplots, Scatterplots and bubble plots, Heatmaps, Time series plots. Visualization in SPSS tool. 

Unit-5
Teaching Hours:14
Statistical Hypothesis Testing
 

Concepts of statistical hypothesis, Null and Alternative hypothesis, Hypothesis testing for population parameters with large samples, Fisher’s Z- transformation for population correlation coefficient(s) and testing the same in case of one sample and two samples.

Hypothesis testing with small samples: Tests of significance based on Chi-square, t and F distributions: Chi-square test for Population Variance, Goodness of fit & test for independence of attributes. t-test for single mean, difference of means, paired t-test, correlation coefficients. F-test for Population Variances, Non-parametric hypothesis testing.

Text Books And Reference Books:
  1. Piegorsch, Walter W. Statistical data analytics: foundations for data mining, informatics, and knowledge discovery. John Wiley & Sons, 2015.
  2. Hinton, Perry R., Isabella McMurray, and Charlotte Brownlow. SPSS explained. Routledge, 2014.
Essential Reading / Recommended Reading
  1. Wu, James, and Stephen Coggeshall. Foundations of predictive analytics. Chapman and Hall/CRC, 2012.
  2. Marcoulides, George A., and Scott L. Hershberger. Multivariate statistical methods: A first course. Psychology Press, 2014.
  3. Morgan, George A., et al. IBM SPSS for introductory statistics: Use and interpretation. Routledge, 2012.
Evaluation Pattern

·         Continuous Internal Assessment (CIA): 70% (70 marks out of 100 marks)

·         End Semester Examination (ESE): 30% (30 marks out of 100 marks)

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

 

·

To study the fundamentals of digital circuits and concepts used in the analysis and design of various digital systems.

Course Outcome

CO1: Describe the characteristics of various digital integrated circuit families, logic gates and classify digital circuits based on their construction. L2:Understand

CO2: Demonstrate the methods of minimization of complex circuits using Boolean Algebra.L3: Apply

CO3: Interpret the methods of Designing combinational circuit.L3: Apply

CO4: Illustrate the methods of Designing sequential circuits.L3: Apply

CO5: Analyze the digital circuits design using VHDL.L4:Analyze

Unit-1
Teaching Hours:9
INTRODUCTION
 

Switching Theory: Laws of Boolean algebra, Theorems of Boolean algebra, Switching functions, Methods for specification of switching functions - Truth tables and Algebraic forms, Realization of functions using logic gates. Digital Logic Elements: Electronic logic gates, Positive and negative logic, Logic families -TTL, ECL and CMOS, Realization of logic gates.

Unit-2
Teaching Hours:9
BOOLEAN ALGEBRA
 

Simplification of Boolean Expressions and Functions: Algebraic methods,     Canonical forms of Boolean functions, Minimization of functions using Karnaugh     maps, Minimization of functions using Quine-McClusky method.

Unit-3
Teaching Hours:9
COMBINATIONAL CIRCUITS
 

Design of Combinational Logic Circuits: Gate level design of Small Scale     Integration (SSI) circuits, Modular combinational logic elements - Decoders,     Encoders, Priority encoders, Multiplexers and Demultiplexers. Design of Integer     Arithmetic Circuits using Combinational Logic: Integer adders - Ripple carry adder     and Carry look ahead adder, Integer subtractors using adders, Unsigned integer     multipliers - Combinational array circuits, Signed integer multipliers - Booth's     coding, Bit-pair recoding, Carry save addition and Wallace tree multiplier, Signed     integer division circuits - Combinational array circuits, Complexity and propagation     delay analysis of circuits. Design of Combinational Circuits using Programmable     Logic Devices (PLDs): Programmable Read Only Memories (PROMs),     Programmable Logic Arrays (PLAs), Programmable Array Logic (PAL) devices,     Design of multiple output circuits using PLDs.

Unit-4
Teaching Hours:9
SEQUENTIAL CIRCUITS
 

Sequential Circuit Elements: Latches -RS latch and JK latch, Flip-flops-RS, JK, T     and D flip flops, Master-slave flip flops, Edge-triggered flip-flops. Analysis and     Design of Synchronous Sequential Circuits: Models of sequential circuits - Moore     machine and Mealy machine, Flip-flops - Characteristic table, Characteristic     equation and Excitation table, Analysis of sequential circuits- Flipflop input     expressions, Next state equations, Next state maps, State table and State transition     diagram, Design of sequential circuits - State transition diagram, State table, Next     state maps, Output maps, Expressions for flip-flop inputs and Expressions for circuit     outputs, Modular sequential logic circuits- Shift registers, Registers, Counters and  Random access memories, Design using programmable logic sequencers (PLSs).     Design of Arithmetic Circuits using Sequential Logic : Serial adder for integers,     Unsigned integer multiplier, Unsigned integer division circuits, Signed integer     division, Floating-pint adder/subtractor - Design of control circuit, Floating - point multiplier.

Unit-5
Teaching Hours:9
CASE STUDY AND INFORMAL LABORATORY
 

Case study: Learn the Fundamentals of Digital Logic Design with VHDL Informal Laboratory:

·         Design and implementation of binary adder / subtractor using basic gates

·         Design and implementation of applications using multiplexers

·         Design and implementation of Synchronous & Asynchronous Counters

·         Design and implementation of Shift Registers

Coding Combinational Circuits using Hardware Description Language (HDL)

Text Books And Reference Books:

T1 - Donald P Leach, Albert Paul Malvino&GoutamSaha, “Digital Principles and Applications” , Tata McGraw Hill 7th Edition, 2010.

 

Essential Reading / Recommended Reading

R1 -Stephen Brown. ZvonkoVranesic, “Fundamentals of Digital Logic Design with VHDL”, Tata McGraw Hill, 2nd Edition 2005.

R2- R D Sudhaker Samuel, “Illustrative Approach to Logic Design. Sanguine-Pearson”, 2010.

R3- Charles H. Roth, “Fundamentals of Logic Design”, Cengage Learning, 5th Edition, 2004.

R4- Ronald J. Tocci, Neal S. Widmer. Gregory L. Moss, “Digital Systems Principles and     Applications, ” 10th  Edition. Pearson Education, 2007

R5- M Morris Mano, “Digital Logic and Computer Design”, Pearson Education, 10th Edition, 2008.

 

Evaluation Pattern

Assessment is based on the performance of the student throughout the semester.

Assessment of each paper

·         Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out

of 100 marks)

·         End Semester Examination(ESE) : 50% (50 marks out of 100 marks)

Components of the CIA

CIA I   :   Mid Semester Examination (Theory)                    : 25 marks                  

CIA II  :  Assignments                                                            : 10 marks

CIA III            : Quizzes/Seminar/Case Studies/Project Work     : 10 marks

Attendance                                                                             : 05 marks

            Total                                                                                         : 50 marks

For subjects having practical as part of the subject

 

Assessment of Practical paper

Conduct of experiments                                                       : 25 marks

Observations/Lab Record                                                   : 15 marks

Viva voce                                                                                : 10 marks

Total                                                                                        : 50 marks

(All the above assessments are carried for each experiment during regular lab classes and averaged to max 50 marks at the end of the semester)

HS311 - TECHNICAL WRITING (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

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.

Course Outcome

CO1: Understand the basics of technical communication and the use of formal elements of specific genres of documentation

CO2: Demonstrate the nuances of technical writing, with reference to English grammar and vocabulary

CO3: Recognize the importance of soft skills and personality development for academic and professional success.

CO4: Understand various techniques involved in oral communication and its application in the professional contexts.

CO5: Realize the importance of having ethical work habits and professional etiquettes.

Unit-1
Teaching Hours:6
Introduction to Technical Communication
 

Communication Process, Flow, Barriers. Analyzing different kinds of technical documents, Reports/Engineering reports – Types, Importance and Structure of formal reports, information and document design.

Unit-2
Teaching Hours:6
Technical Writing
 

Vocabulary for professional writing. Idioms and collocations, Writing drafts and revising, writing style and language. Writing Emails, Resumes, Video resume, Interviews, Types of interviews.

Unit-3
Teaching Hours:6
Soft Skills
 

Self development process, Personality development, Types of personality, Perception and attitudes, Emotional intelligence, Time Management, Values and beliefs, Personal goal setting, Creativity, Conflict management, Career planning. 

Unit-4
Teaching Hours:6
Professional Presentation Skills
 

Writing a speech, Formal presentations, Public speaking, Presentation aids, Group communication, Discussions, Organizational GD, Meetings & Conferences.

Unit-5
Teaching Hours:6
Professional Etiquette
 

Email etiquettes, Telephone Etiquettes, Engineering ethics, Role and responsibility of engineer, Work culture in jobs.

Text Books And Reference Books:

T1: David F. Beer and David McMurrey, Guide to writing as an Engineer, John Willey. New York, 2004

T2: Diane Hacker, Pocket Style Manual, Bedford Publication, New York, 2003. (ISBN 0312406843)

T3: Raman Sharma, Technical Communications, Oxford Publication, London, 2004 

Essential Reading / Recommended Reading

R1. Dale Jungk, Applied Writing for Technicians, McGraw Hill, New York, 2004. (ISBN: 07828357-4)

R2. Sharma, R. and Mohan, K. Business Correspondence and Report Writing, TMH New Delhi 2002.

R3. Xebec, Presentation Book, TMH New Delhi, 2000. (ISBN 0402213)

Evaluation Pattern

Evaluation Pattern:

CIA 50 Marks

ESE 50 Marks

CIA 1 Quiz/Assignment/Grammar Test/Oral Talk

CIA 2 Mid Semester Exam: MSE CIA

3 Presentation/Mini Project/Portfolio

MA334 - DISCRETE MATHEMATICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

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. 

Course Outcome

CO1: Distinguish the compound logical statements and validate arguments with logical connectives. [L2]

CO2: Solve Lattices and Boolean algebra problems using partial order set . [L3]

CO3: Compute coding and decoding problems using group theory and appropriate coding and decoding schemes. [L3]

CO4: Classify types of functions/permutation functions as even or odd and solve problems on inverse functions. [L2]

CO5: Solve problems related to recurrence using various techniques of counting. [L3]

Unit-1
Teaching Hours:9
Propositional Calculus:
 

Propositions – Logical connectives – Compound propositions – Conditional and bi conditional propositions – Truth tables – Tautologies and contradictions – Contrapositive – Logical equivalences and implications – De Morgan’s Laws - Normal forms, Rules of inference – Arguments - Validity of arguments.

Unit-2
Teaching Hours:9
Set Theory
 

Basic concepts of Sets - Subset – Algebra of sets – The power set – Ordered pairs and Cartesian product – Relations on sets –Types of relations and their properties – Matrix and Graph representation of a relation – Partial ordering – Poset – Hasse diagram – Lattices and their properties – Sublattices – Boolean algebra.

Unit-3
Teaching Hours:9
Group Theory and Coding
 

Properties – Subgroups - Cosets and Lagrange’s theorem – Normal subgroups – Algebraic system with two binary operations – Preliminaries of Coding -  Hamming Metric  - group codes: –  Basic notions of error correction - Error recovery in group codes.

Unit-4
Teaching Hours:9
Counting Techniques-I
 

Types of functions - Examples – Composition of functions – Inverse functions – Characteristic function of a set, Mathematical Induction, The Rules of Sum and Product, Permutations, Combinations.

Unit-5
Teaching Hours:9
Counting Techniques-II
 

Fundamental principles of counting, pigeonhole principle, principle of inclusion and exclusion, Solving Linear Recurrence Relations, Divide-and-Conquer Algorithms and Recurrence Relations, generating functions, Solve Recurrence Relations using Generating Functions.

Text Books And Reference Books:

Text Books

T1. Trembly J.P and Manohar R, Discrete Mathematical Structures with Applications to Computer Science, Tata McGrawHill Pub.Co. Ltd, New Delhi, 2003. 

T2. Ralph. P. Grimaldi, Discrete and Combinatorial Mathematics: An Applied Introduction, Fifth Edition, Pearson Education Asia,Delhi, 2009.

Essential Reading / Recommended Reading

Reference Books 

1.      R1. Bernard Kolman, Robert C. Busby, Sharan Cutler Ross, Discrete Mathematical Structures,  Fourth Indian reprint, Pearson Education Pvt Ltd., New Delhi, 2003.

2.      R2. Kenneth H. Rosen, Discrete Mathematics and its Applications, Fifth Edition, Tata McGraw Hill Pub. Co. Ltd., New Delhi, 2003.

3.      R3. Richard Johnsonbaugh, Discrete Mathematics, Fifth Edition,Pearson Education Asia, New Delhi, 2002.


Evaluation Pattern

Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks)

End Semester Examination(ESE)      : 50% (50 marks out of 100 marks) 

  

S.No

Assessment

Marks

Weightagemarks

1

CIA I

20

10

2

CIA II

     (MSE: Mid Semester Examination)

50

25

3

CIA III

20

10

4

Attendance

10

05

5

ESE

(End Semester Examination)

100

50

Total

100

Components of the CIA

CIA I  :  Subject Assignments / Online Tests                  : 10 marks

CIA II :   Mid Semester Examination (Theory)                : 25 marks            

CIAIII: Quiz/Seminar/Innovative Assignments/presentations/publications : 10 marks

Attendance                                                                           : 05 marks

            Total                                                                                       : 50 marks

Mid Semester Examination (MSE) : Theory Papers:

  • The MSE is conducted for 50 marks of 2 hours duration.
  • Question paper pattern; Four questions have to be answered in part A without any choice. One question need to be answered out of two in part B. Each  question carries 10 marks

End Semester Examination (ESE):

The ESE is conducted for 100 marks of 3 hours duration.

The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.

Question paper pattern is as follows.

Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

The criteria for drawing the questions from the Question Bank are as follows

50 % - Medium Level questions

25 % - Simple level questions

25 % - Complex level questions

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

 

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. 

Course Outcome

CO1: To familiarize students with general computer programming concepts like conditional execution, functions, loops.

CO2: To learn and understand Python programming language syntax, semantics, and the Runtime environment, as well as with general coding techniques and object-oriented programming.

Unit-1
Teaching Hours:30
Basics level Python
 

Introduction to Python and Computer Programming, Data Types, Variables, Basic, Input-Output Operations, Basic Operators,Boolean Values, Conditional Execution, Loops, Lists and ListProcessing, Logic and BitwiseOperations, Functions, Tuples, Dictionaries, and Data Processing.

 

Unit-2
Teaching Hours:30
Intermediate level Python
 

Exceptions, Strings, String and List Methods,Object Oriented Programming in Python,Working with filesystem, Directory trees and Files,Selected Python Standard Library modules (os, date, datetime,calendar).

Text Books And Reference Books:

 https://www.netacad.com/courses/programming/pcap-programming-essentials-python

Essential Reading / Recommended Reading

 https://www.netacad.com/courses/programming/pcap-programming-essentials-python

Evaluation Pattern

Online Assessment

VCSE314 - JAVA PROGRAMMING (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:0

Course Objectives/Course Description

 

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. 

Course Outcome

CO1: Utilize java core concepts to solve any real world problems.

Unit-1
Teaching Hours:60
Java Programming
 

Getting Started with Eclipse, Object and Driver Classes,  Data Types and Operators, Strings, Program Structure, Scanner and Conditional Statements, Control Statements, Arrays, Classes, Objects, and Methods - Parameters and Overloading Methods, The Static Modifier and Nested Classes,  Inheritance , Polymorphism, Generics, Collections ,  Sorting and Searching using Collection, String Class, String methods, Regular Expressions, Basics of Input and Output , Input and Output Fundamentals • Deploying an Application, JDBC Introduction.

Text Books And Reference Books:

https://academy.oracle.com/en/

Essential Reading / Recommended Reading

https://academy.oracle.com/en/

Evaluation Pattern

Online assessment

VCSE315 - RED HAT CERTIFIED SYSTEM ADMINISTRATOR (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:0

Course Objectives/Course Description

 

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 

Course Outcome

CO1: Students be able to perform essential Linux system administration tasks. Establishing network connectivity, managing physical storage, and basic security administration

CO2: Students can perform the key tasks like firewall configuration, troubleshooting etc., needed to become Linux administrators.

Unit-1
Teaching Hours:30
Get started with Red Hat Enterprise Linux
 

Get started with Red Hat Enterprise LinuxDescribe and define open source, Linux, Linux distributions, and Red Hat Enterprise LinuxAccess the command lineLog into a Linux system and run simple commands using the shell.Manage files from the command lineCopy, move, create, delete, and organize files while working from the bash shell.Get help in Red Hat Enterprise LinuxResolve problems by using local help systems.Create, view, and edit text filesManage text files from command output or in a text editor.Manage local users and groupsCreate, manage, and delete local users and groups, as well as administer local password policies.Control access to filesSet Linux file system permissions on files and interpret the security effects of different permission settings.Monitor and manage Linux processesEvaluate and control processes running on a Red Hat Enterprise Linux system.Control services and daemonsControl and monitor network services and system daemons with the systemd service.Configure and secure SSHConfigure secure command line service on remote systems, using OpenSSH.Analyze and store logsLocate and accurately interpret logs of system events for troubleshooting purposes.Manage networkingConfigure network interfaces and settings on Red Hat Enterprise Linux servers.Install and update software packagesDownload, install, update, and manage software packages from Red Hat and DNF package repositories.Access Linux files systemsAccess, inspect, and use existing file systems on storage attached to a Linux server.Analyze servers and get supportInvestigate and resolve issues in the web-based management interface, getting support from Red Hat to help solve problems.Comprehensive reviewReview the content covered in this course by completing hands-on exercises.

Unit-2
Teaching Hours:30
Improve command line productivity
 

Improve command line productivityRun commands more efficiently by using advanced features of the Bash shell, shell scripts, and various utilities provided by Red Hat Enterprise Linux.Schedule future tasksSchedule commands to run in the future, either one time or on a repeating schedule.Analyze and Store LogsLocate and accurately interpret system event logs for troubleshooting purposes.Archive and Transfer FilesArchive and copy files from one system to another.Tune system performanceImprove system performance by setting tuning parameters and adjusting scheduling priority of processes.Manage SELinux securityProtect and manage the security of a server by using SELinux.Manage logical volumesCreate and manage logical volumes containing file systems and swap spaces from the command line.Access network-attached storageUse the NFS protocol to administer network-attached storage.Control the boot processManage the boot process to control services offered and to troubleshoot and repair problems.Manage network securityControl network connections to services using the system firewall and SELinux rules.Install Red Hat Enterprise LinuxInstall Red Hat Enterprise Linux on servers and virtual machines.Run ContainersObtain, run, and manage simple, lightweight services as containers on a single Red Hat Enterprise Linux server.

Text Books And Reference Books:

Redhat Couse Meterials

Essential Reading / Recommended Reading

Redhat Couse Meterials

Evaluation Pattern

CIA 

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

 

 

Course objectives:  This course is an overview of different types of operating systems. They also include understanding of the components of an operating system, process management, and knowledge of storage management and the concepts of I/O and file systems is also covered as an introductory level.

Course Outcome

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.

Unit-1
Teaching Hours:9
INTRODUCTION
 

Introduction : What operating systems do, Computer System Architecture, Operating System Structure, Operating System Operations, Process Management,  Memory Management, Storage Management, Protection and Security; System Structures: Operating System Services, User Operating System Interface, System Calls, Types of System Calls.

Unit-2
Teaching Hours:9
PROCESS MANAGEMENT
 

Process Management: Process Concept, Process Scheduling, Operations on Processes, Inter-process Communication; Threads: Overview, Multithreading Models, Thread Libraries; CPU Scheduling: Basic Concepts, Scheduling Criteria, Scheduling Algorithms, Multiple- Processor Scheduling

Unit-3
Teaching Hours:9
PROCESS SYNCHRONIZATION AND DEADLOCKS
 

Process Synchronization: Background, The Critical Section Problem, Peterson’s Solution, Synchronization Hardware, Semaphores, Classical Problems of Synchronization, Monitors, Synchronization Examples, Deadlocks

Unit-4
Teaching Hours:9
MEMORY MANAGEMENT AND VIRTUAL MEMORY
 

Memory Management: Background, Swapping, Contiguous Memory Allocation, Paging.

 

Virtual Memory : Background, Demand Paging, Copy on Write, Page Replacement, Allocation of frames, Thrashing, Allocating Kernel Memory

Unit-5
Teaching Hours:9
FILE SYSTEM INTERFACE AND FILE SYSTEM IMPLEMENTATION & MASS STORAGE STRUCTURE
 

File System Interface: File System: File Concept, Access Methods, Directory Structure, File System Mounting, File Sharing, Protection.

 

File System Implementation & Mass Storage Structure: Implementing File Systems: File System Structure, File System Implementation, Directory Implementation, Allocation Methods, Free Space Management. Disk structure, Disk Attachment, Disk Scheduling Methods, Disk Management, Swap-Space Management

Text Books And Reference Books:

1. Abraham Silberschatz, , Peter Baer Galvin and Greg Gagne “Operating System  Concepts”, John Wiley & Sons (ASIA) Pvt. Ltd,Tenth Edition ,2018.

2. Harvey M. Deitel, “Operating Systems”, Pearson Education Pvt. Ltd, Third Edition, 2008.

Essential Reading / Recommended Reading

R1. Andrew S. Tanenbaum, “Modern Operating Systems”, Prentice Hall of India Pvt. Ltd, Fourth Edition 2016.

R2. William Stallings, “Operating System- Internals and Design Principles”, Pearson Education, Nineth Edition, 2018.

R3. Pramod Chandra P. Bhatt – “An Introduction to Operating Systems, Concepts and Practice”, PHI, Fifth Edition, 2019.

Evaluation Pattern

CIA  70 marks

ESE 30 Marks

CS433P - PROGRAMMING PARADIGM (2022 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

 

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.

Course Outcome

CO 1: Demonstrate the fundamental concepts of Object-Oriented Programming.

CO 2: Make use of the inheritance and interface concepts for effective code reuse.

CO 3: Develop dynamic and interactive graphical applications using AWT and SWING

CO 4: Examine the generic programming and exception handling concepts.

CO 5: Interpret the importance of multi-threading concepts to develop concurrent applications.

Unit-1
Teaching Hours:9
OBJECT-ORIENTED PROGRAMMING ? FUNDAMENTALS
 

 

Review of OOP - Objects and classes in Java – defining classes – methods - access specifiers – static members – constructors – finalize method – Arrays – Strings - Packages – JavaDoc comments.

Unit-2
Teaching Hours:9
OBJECT-ORIENTED PROGRAMMING ? INHERITANCE
 

Inheritance – class hierarchy – polymorphism – dynamic binding – final keyword – abstract classes – the Object class – Reflection – interfaces – object cloning – inner classes

Unit-3
Teaching Hours:9
EVENT-DRIVEN PROGRAMMING
 

 

Graphics programming – Frame – Components – working with 2D shapes – Using color, fonts, and images - Basics of event handling – event handlers – adapter classes – actions – mouse events – AWT event hierarchy – introduction to Swing – Model-View- Controller design pattern – buttons – layout management – Swing Components

Unit-4
Teaching Hours:9
GENERIC PROGRAMMING
 

 

Motivation for generic programming – generic classes – generic methods – generic code and virtual machine – inheritance and generics – reflection and generics – exceptions – exception hierarchy – throwing and catching exceptions.

Unit-5
Teaching Hours:9
CONCURRENT PROGRAMMING
 

 

Multi-threaded programming – interrupting threads – thread states – thread properties – thread synchronization – thread-safe Collections – Executors – synchronizers – threads and event-driven programming, Parallel programming –fork, join framework.

Text Books And Reference Books:

T1. Cay S. Horstmann and Gary Cornell, “Core Java, Volume I – Fundamentals”, Eleventh Edition, Prentice Hall, 2018.

Essential Reading / Recommended Reading

 

R1. Herbert Schildt,  “Java: The Complete Reference (Complete Reference Series)”, Eleventh Edition, 2020.

R2. Cay S. Horstmann , “Java SE8 for the Really Impatient: A Short Course on the  Basics (Java Series)”, 2014.

R3. Bruce Eckel, “Thinking in Java”, 4th Edition, Prentice Hall Professional, 2006.

R4. Doug Rosenberg and Matt Stephens, “Use Case Driven Object Modeling with UML: Theory and Practice (Expert's Voice in UML Modeling)”,APress, 2013.

 

R5.Martina Seidl, Marion Scholz, Christian Huemer and GertiKappel , “UML @ Classroom An Introduction to Object-Oriented Modeling Series: Undergraduate Topics in Computer Science”, Springer, 2015

Evaluation Pattern

CIA - 70 Marks

ESE - 30 Marks

CS434 - FORMAL LANGUAGE AND AUTOMATA THEORY (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

 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.

Course Outcome

CO1: Design finite automata with conversion between types of finite automata.

CO2: Develop regular expression and minimize the given finite automata for any regular language.

CO3: Develop context free grammar, parse trees and pushdown automata for a given context free language.

CO4: Experiment with CFLs and design of Turing machine for a given language.

CO5: Explain decidable and undecidable problems, solvable and unsolvable problems with their complexity analysis.

Unit-1
Teaching Hours:9
AUTOMATA
 

Automata - Introduction to formal proof – Additional forms of proof – Inductive proofs –Finite Automata (FA) – Central concepts of Automata Theory, Representation of Automata, Deterministic Finite Automata (DFA) – Non-deterministic Finite Automata (NFA) – Finite Automata with Epsilon transitions. Introduction to automata simulation tools

Unit-2
Teaching Hours:9
REGULAR EXPRESSIONS AND LANGUAGES
 

Regular Expressions and Languages 

 

Regular Expression – FA and Regular Expressions – Proving languages not to be regular – Closure properties of regular languages – Equivalence and minimization of Automata.

Unit-3
Teaching Hours:9
CONTEXT-FREE GRAMMAR AND LANGUAGES
 

Context-Free Grammar and Languages  

 

Context-Free Grammar (CFG) – LMD, RMD, Parse Trees – Ambiguity in grammars and languages – Definition of the Pushdown automata – Languages of a Pushdown Automata, Designing of a PDA and string acceptance – Equivalence of Pushdown automata and CFG, Non-Deterministic Pushdown Automata.

Unit-4
Teaching Hours:9
PROPERTIES OF CONTEXT-FREE LANGUAGES
 

Properties of Context-Free Languages  

 

Simplifications of CFG, Normal forms for CFG – Pumping Lemma for CFL - Closure Properties of CFL – Turing Machines – Definition, Problems, Language accepted, String acceptance, Programming Techniques for TM.

Unit-5
Teaching Hours:9
UNDECIDABILITY
 

Undecidability  

 

A language that is not Recursively Enumerable (RE) – An undecidable problem that is RE – Undecidable problems about Turing Machine – Post’s Correspondence Problem - The classes P and NP, Linear Bounded Automata - Definition and examples

Text Books And Reference Books:

1. J.E.Hopcroft, R.Motwani and J.D Ullman, “Introduction to Automata Theory, Languages and Computations”, Pearson Education, 2008.

 

2. Peter Linz  “An Introduction to formal languages and automata”, sixth edition, Jones and Bartlett Learning, 2016.

Essential Reading / Recommended Reading

1. H.R.Lewis and C.H.Papadimitriou, “Elements of The theory of Computation”, Second Edition, Pearson Education/PHI, 2003.

2. J.Martin, “Introduction to Languages and the Theory of Computation”, 3rd Edition, TMH, 2003.

3. MichealSipser, “Introduction of the Theory and Computation”, Thomson Brokecole, 3rd Edition, 1997

Evaluation Pattern

Contnuous Internal Assessment - 50 Marks

End Semester Exam - 50 Marks

CS435P - COMPUTER ORGANIZATION AND ARCHITECTURE (2022 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

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

Course Outcome

CO1: Demonstrate the functions of basic components of computer system and Instruction set Architecture

CO2: Select suitable arithmetic algorithm to solve given arithmetic and logical problems

CO3: Utilize appropriate instruction level parallelism concepts in multiprocessing environment

CO4: Identify suitable control unit design and pipelining principles in computer architecture design

CO5: Choose suitable memory and I/O system design

Unit-1
Teaching Hours:9
FUNDAMENTALS OF COMPUTER SYSTEM
 

Functional Units – Basic Operational Concepts – Performance – Instructions: Language of the Computer – Operations, Operands – Instruction representation – Logical operations – decision making – MIPS Addressing.

Unit-2
Teaching Hours:9
COMPUTER ARTHIMETIC
 

Addition and Subtraction – Multiplication – Division – Floating Point Representation – Floating Point Operations – Subword Parallelism

Unit-3
Teaching Hours:9
BASIC PROCESSING AND CONTROL UNIT
 

A Basic MIPS implementation – Building a Datapath – Control Implementation Scheme – Pipelining – Pipelined data path and control – Handling Data Hazards & Control Hazards – Exceptions.

Unit-4
Teaching Hours:9
PARALLELISM
 

Parallel processing challenges – Flynn‘s classification – SISD, MIMD, SIMD, SPMD, and Vector Architectures - Hardware multithreading – Multi-core processors and other Shared Memory Multiprocessors - Introduction to Graphics Processing Units, Clusters, Warehouse Scale Computers and other Message-Passing Multiprocessors.

Unit-5
Teaching Hours:9
MEMORY AND I/O
 

Memory Hierarchy - memory technologies – cache memory – measuring and improving cache performance – virtual memory, TLB‘s – Accessing I/O Devices – Interrupts – Direct Memory Access – Bus structure – Bus operation – Arbitration – Interface circuits - USB.

Text Books And Reference Books:

Text Books:

T1. David A. Patterson and John L. Hennessy, “Computer Organization and Design: The Hardware/Software Interface”, Fifth Edition, Morgan Kaufmann / Elsevier, 2014.

T2. Carl Hamacher, ZvonkoVranesic, SafwatZaky and NaraigManjikian, “Computer Organization and Embedded Systems”, Sixth Edition, Tata McGraw Hill, 2012.

Essential Reading / Recommended Reading

Reference Books:

R1. William Stallings, “Computer Organization and Architecture – Designing for Performance”, Sixth Edition, Pearson Education, 2003.

R2.  John L. Hennessey and David A. Patterson, “Computer Architecture –A Quantitative Approach”, Fifth Edition, Morgan Kaufmann / Elsevier Publishers,2012.

Evaluation Pattern

CIA  - 70% out of 100

ESE - 30% out of 100

CSHO432AIP - ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (2022 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Course Description:

This course offers a solid foundation of key ideas in machine learning. The objective is to impart expertise on using Python packages related to Machine Learning and supervised and unsupervised techniques.

 

Course Objective:

1. To gain knowledge in the basics of Python Machine Learning Libraries.

2. To analyze the applicability, benefits, and drawbacks of the Supervised and Unsupervised machine learning techniques.

3. To acquire knowledge on the recommendation systems and their working methodology

Course Outcome

CO1: Explain Forms of Learning and demonstrate the fundamental machine learning operations in Python.

CO2: Examine different machine learning regression techniques.

CO3: Analyze supervised classification methods.

CO4: Inspect various unsupervised clustering techniques.

CO5: Outline the concept of recommendation systems for real-time problems.

Unit-1
Teaching Hours:9
Unit 1 Learning
 

Artificial Intelligence - Introduction to Artificial Intelligence, Machine Learning, Deep Learning, Applications of Artificial Intelligence, Learning Agent.

Forms of Learning - Supervised Learning, Unsupervised Learning, Semi supervised Learning, Reinforcement Learning

Python libraries suitable for Machine Learning - Numpy, Pandas, Data visualization using matplotlib, sklearn.

Unit-2
Teaching Hours:9
Unit 2 Supervised Learning - Regression
 

Linear and Non Linear regression -Simple Linear regression,Multiple Linear Regression -

Multivariate Linear regression -Model Evaluation Methods(Loss Function, the cost function,

Residual Errors and Mean Square Error(MSE))-Applications of Regression.

Unit-3
Teaching Hours:9
Unit 3 Supervised Learning - Classification
 

K-Nearest Neighbors - Decision Tree - Support Vector Machines -Logistic RegressionClassification Metrics (Confusion Matrix, Accuracy, Precision Recall (Sensitivity), F1 Score, Area Under the Curve-Receiver Operator Characteristic (AUC-ROC))-Applications of classification

 

Unit-4
Teaching Hours:9
Unit 4 UnSupervised Learning - Clustering
 

K-means clustering - Hierarchical clustering, Agglomerative Hierarchical clustering,Types of linkage - Density-Based Clustering,DBSCAN-Applications of Clustering

 

Unit-5
Teaching Hours:9
Unit 5 Recommender Systems
 

Recommendation System,Content-based filtering,Collaborative filtering,Hybrid - Real time case studies on Recommender Systems.

 

Text Books And Reference Books:

T1. Andreas C. Müller, Sarah Guido , “Introduction to Machine Learning with Python”,O'Reilly Media, Inc.,First Edition, September 2016,ISBN: 9781449369897.

T2. Sebastian Raschka, Vahid Mirjalili, “Python Machine Learning - Third Edition”, O'Reilly Media, Inc.,Third Edition, December 2019, ISBN: 9781789955750.

Essential Reading / Recommended Reading

R1. Manaranjan Pradhan, U. Dinesh Kumar, “ Machine Learning Using Python”, Wiley india Pvt. Ltd, 2019 Edition, ISBN: 9788126579907.

R2. Wes McKinney, ”Python for Data: Data Wrangling with Pandas, NumPy, and IPython”, Second Edition,O′Reilly, 2017.

R3. John Paul Mueller, Luca Massaron, “Machine Learning For Dummies”, John Wiley & Sons, Inc., 2016.

R4. Tom M. Mitchell, Machine Learning, McGraw-Hill Education (India) Private Limited, 2013.

R5. Kevin Murphy, Machine Learning: A Probabilistic Perspective, MIT Press, 2012.

Evaluation Pattern

CIA: 50

ESE: 50

CSHO432CSP - MOBILE AND NETWORK BASED ETHICAL HACKING (2022 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

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.

Course Outcome

CO1: To describe the vulnerability scanning for networks.

CO2: To understand the information-gathering modes for any attack on the network.

CO3: To demonstrate different hacking processes and corresponding attacks for mobile platforms.

CO4: To interpret means to evade firewalls and other security parameters for ethical hacking.

CO5: To apply various possible tools for different vulnerabilities that are exploited for hacking.

Unit-1
Teaching Hours:9
Unit 1
 

Introduction to ethical hacking, IP addressing, Network routing protocols, network security, network scanning, vulnerability assessment OpenVAS, Nessus, etc. of computation device (Mobile, PC, etc.) and system network.

 

Unit-2
Teaching Hours:9
Unit 2
 

Computation system hacking, modes of gathering information, password cracking, penetration testing including backdoor issues, Malware threats, and different cyber-related attacks.

Unit-3
Teaching Hours:9
Unit 3
 

Introduction to Mobile Hacking, encryption types and attacks, different mobile platforms, and corresponding vulnerabilities.

 

Unit-4
Teaching Hours:9
Unit 4
 

Evading firewalls, standard detection systems and frameworks, and other possible attack detection methods.

 

Unit-5
Teaching Hours:9
Unit 5
 

Case studies: various hacking scenarios, information gathering, and possible solutions.

 

Text Books And Reference Books:

T1. McNab, Chris. Network security assessment: know your network. " O'Reilly Media, Inc.", 2007.

T2. Weidman, Georgia. Penetration testing: a hands-on introduction to hacking. No Starch Press, 2014.

T3. Engebretson, Patrick. The basics of hacking and penetration testing: ethical hacking and penetration testing made easy. Elsevier, 2013.

T4. Dwivedi, Himanshu. Mobile application security. Tata McGraw-Hill Education, 2010.

 

Essential Reading / Recommended Reading

https://nmap.org- Open Source Network Scanning tool.

https://www.openvas.org open source tool, network vulnerability scanner

Hacking: The Art of Exploitation

Metasploit: The Penetration Tester's Guide

Metasploit, Nessus, Recon-ng, Better cap, Ettercap, Open-Vas, Burp-suit, Hydra, Medusa, Air crack-ng.

Evaluation Pattern

CIA-50

ESE-50

DS451 - PYTHON FOR DATA SCIENCE (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:100
Credits:1

Course Objectives/Course Description

 

 

  • To understand the fundamentals of Python Programming

  • To apply Python Programming Constructs for solving real life problems in the domain of engineering , business, health care, and other social applications.

Course Outcome

CO 1: To summarize the fundamentals of Python Programming Constructs for problem solving.

CO2: To make use of Control flow and Functions for solving problems

CO 3: To utilize List, Modules and Packages to develop solutions for real life problems.

CO 4: To build solutions of real life use cases using Files, Modules and Packages through data processing and analysis.

CO 5: To analyse, visualize and perform predictive modelling of data using Python.

Unit-1
Teaching Hours:6
INTRODUCTION TO PYTHON
 

 

Installing a complete Python environment, Python Introduction, Keywords and Identifiers, Statements and comments, Python Data types, Python I/O and import, Python Operators, Basic Mathematics, Variables, Strings and text, Interacting with users. Illustrative Programs using Variables and Data Types: Numeric, Lists, Strings, tuples, Sets, and Dictionary; Illustrative Programs using Operators:  Arithmetic, Comparison, Assignment, Logical, Bitwise, Membership, and Identity.

Unit-2
Teaching Hours:6
CONTROL FLOW AND FUNCTIONS
 

Looping and logic , Python Flow Control, if-else, for loop, while loop, break and continue , Illustrative programs. Python Functions, Python Functions, function argument, python recursion, python module, python package Illustrative Programs using Conditional Statements:  If, Elif and Else; Loops:  While, for and nested loops; Functions: 

Unit-3
Teaching Hours:6
DATA STRUCTURES
 

 

Data structures using lists, Tuple and dictionaries; Lists: list operations, list slices, list methods, list loop, mutability, Tuples; Dictionaries: operations and methods;

Unit-4
Teaching Hours:6
FILES , MODULES, PACKAGES
 

 

Files: text files, reading and writing files, format operator; modules, packages; Illustrative programs: word count, copy

Unit-5
Teaching Hours:6
PYTHON FOR DATA ANALYSIS AND APPLICATIONS
 

Python Basics For Data Analysis and Visualization: Loading , Cleaning and Exploring and Visualization.Python Libraries For Data Science (Numpy ,Pandas , Matplotlib, Seaborn ,Scikit-Learn),  Data Science and Machine Learning  – Use Cases- Case studies: Targeted Advertising, Healthcare, Speech Recognition, Website Recommendations, Image Recognition, Fraud and Risk Detection

Text Books And Reference Books:

T1. Allen B. Downey, ``Think Python: How to Think Like a Computer Scientist’’, 2nd edition, Updated for Python 3, Shroff/O’Reilly Publishers, 2017 

 

T2. Guido van Rossum and Fred L. Drake Jr, “An Introduction to Python – Revised and updated for Python 3.2, Network Theory Ltd., 2011. (reprint)

Essential Reading / Recommended Reading

R1. Charles Dierbach, “Introduction to Computer Science using Python: A Computational Problem-Solving Focus, Wiley India Edition, 2013.(reprint)

R2. John V Guttag, “Introduction to Computation and Programming Using Python’’, Revised and expanded Edition, MIT Press , 2013(reprint)

R3. Kenneth A. Lambert, “Fundamentals of Python: First Programs”, CENGAGE Learning, 2012.

R4. Paul Gries, Jennifer Campbell and Jason Montojo, “Practical Programming: An Introduction to Computer Science using Python 3”, Second edition, Pragmatic Programmers,LLC,2013.

R5. Robert Sedgewick, Kevin Wayne, Robert Dondero, “Introduction to Programming in Python: An Inter-disciplinary Approach, Pearson India Education Services Pvt. Ltd., 2016.

 

R6. Timothy A. Budd, “Exploring Python”, Mc-Graw Hill Education (India) Private Ltd.,, 2015.

Evaluation Pattern

CIA=50

ESE=50

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

 

To understand the scope and importance of environmental science towards developing a conscious community for environmental issues, both at global and local scale.  

Course Outcome

CO1: Explain the components and concept of various ecosystems in the environment (L2, PO7)

CO2: Explain the necessity of natural resources management (L2, PO1, PO2 and PO7)

CO3: Relate the causes and impacts of environmental pollution (L4, PO1, PO2, and PO3, PO4)

CO4: Relate climate change/global atmospheric changes and adaptation (L4,PO7)

CO5: Appraise the role of technology and institutional mechanisms for environmental protection (L5, PO8)

Unit-1
Teaching Hours:6
Introduction
 

Environment and Eco systems – Definition, Scope and importance. Components of environment. Concept and Structure of eco systems. Material Cycles – Nitrogen, Carbon, Sulphur, Phosphorous, Oxygen. Energy Flow and classification of Eco systems.   

Unit-2
Teaching Hours:6
Natural Resources
 

Classification and importance- Forest, Water, Mineral, Food, Energy. Management of natural resources – challenges and methods. Sustainable development – Goals, Agriculture, Industries

Unit-3
Teaching Hours:6
Environmental Pollution
 

Causes and Impacts – Air pollution, Water pollution, Soil Pollution, Noise Pollution, Marine Pollution, Municipal Solid Wastes, Bio Medical and E-Waste. Solid Waste Management

Unit-4
Teaching Hours:6
Climate change/Global Atmospheric Change
 

Global Temperature, Greenhouse effect, global energy balance, Global warming potential, International Panel for Climate Change (IPCC) Emission scenarios, Oceans and climate change. Adaptation methods. Green Climate fund. Climate change related planning- small islands and coastal region. Impact on women, children, youths and marginalized communities

Unit-5
Teaching Hours:6
Environmental Protection
 

Technology, Modern Tools – GIS and  Remote Sensing,. Institutional Mechanisms - Environmental Acts and Regulations, Role of government, Legal aspects. Role of Nongovernmental Organizations (NGOs) , Environmental Education and Entrepreneurship

Text Books And Reference Books:

T1Kaushik A and Kaushik. C. P, “Perspectives in Environmental Studies”New Age International Publishers, New Delhi, 2018 [Unit: I, II, III and IV]

T2Asthana and Asthana, “A text Book of Environmental Studies”, S. Chand, New Delhi, Revised Edition, 2010 [Unit: I, II, III and V]

T3Nandini. N, Sunitha. N and Tandon. S, “environmental Studies” , Sapana, Bangalore,  June 2019 [Unit: I, II, III and IV]

T4R Rajagopalan, “Environmental Studies – From Crisis to Cure”, Oxford, Seventh University Press, 2017, [Unit: I, II, III and IV]

 

Essential Reading / Recommended Reading

R1.Miller. G. T and Spoolman. S. E, “Environmental Science”, CENAGE  Learning, New Delhi, 2015

R2.Masters, G andEla, W.P (2015), Introduction to environmental Engineering and Science, 3rd Edition. Pearson., New Delhi, 2013.

R3.Raman Sivakumar, “Principals of Environmental Science and Engineering”, Second Edition, Cengage learning Singapore, 2005.

R4.P. Meenakshi, “Elements of Environmental Science and Engineering”, Prentice Hall of India Private Limited, New Delhi, 2006.

R5.S.M. Prakash, “Environmental Studies”, Elite Publishers Mangalore, 2007

R6.ErachBharucha, “Textbook of Environmental Studies”, for UGC, University press, 2005.

R7. Dr. Pratiba Sing, Dr. AnoopSingh and Dr. PiyushMalaviya, “Textbook of Environmental and Ecology”, Acme Learning Pvt. Ltd. New Delhi.

Evaluation Pattern

No Evaluation

HS422 - PROFESSIONAL ETHICS (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Understand the importance of Values and Ethics in their personal lives and professional careers

Course Outcome

CO1: Understand the importance of Values and Ethics in their personal lives and professional careers

CO2: Learn the rights and responsibilities as an employee, team member and a global citizen

CO3: Estimate the impact of self and organization?s actions on the stakeholders and society

CO4: Develop an ethical behaviour under all situations

CO5: Appreciate the significance of Intellectual Property as a very important driver of growth and development in today?s world and be able to statutorily acquire and use different types of intellectual property in their professional life

Unit-1
Teaching Hours:6
Introduction to Ethics
 

Introduction to Professional Ethics : Definition, Nature, Scope- Moral Dilemmas- moral Autonomy-Kohlberg’s theory- Gilligan’s theory, Profession Persuasive, Definitions, Multiple motives, Models of professional goals. Moral Reasoning and Ethical theories – Professional Ideals and Virtues- Theories of Right Action, Self- interest, Customs and Regions- Use of ethical Theories

Unit-2
Teaching Hours:6
Engineering as Social Experimentation and Responsibility
 

Engineering as Social Experimentation and Responsibility For Safety Engineering as experimentation- Engineers as responsible experimenters, the challenger case, Codes of Ethics, A balanced outlook on law. Concept of safety and risk, assessment of safety and risk- risk benefit analysis and reducing the risk- three- mile island, Chernobyl and safe exists.

Unit-3
Teaching Hours:6
Global Issues and Introduction To Intellectual Property
 

Global Issues and Introduction To Intellectual Property - Multinational corporations- Environmental ethics- Computer ethics and Weapons developments. Meaning and Types of Intellectual Property, Intellectual Property. Law Basics, Agencies responsible for intellectual property registration, International Organizations, Agencies and Treaties, Importance of Intellectual Property Rights.

Unit-4
Teaching Hours:6
Foundations of Trademarks
 

Foundations of Trademarks - Meaning of Trademarks, Purpose and Functions of Trademarks, types of Marks, Acquisition of Trademark rights, Common Law rights, Categories of Marks, Trade names and Business Name, Protectable Matter, Exclusions from Trademark Protection.

Unit-5
Teaching Hours:6
Foundations of Copyrights Law
 

Foundations of Copyrights Law - Meaning of Copyrights, Common Law rights and Rights under the 1976 copyright Act, Recent developments of the Copyright Act, The United States Copyright Office

Text Books And Reference Books:

T1. Mike Martin and Roland Schinzinger, “Ethics in Engineering”, McGraw-Hill, New York 1996.

T2. Govindarajan M, Natarajan S, Senthil Kumar V. S, “Engineering Ethics”, Prentice Hall of India,  New  Delhi, 2004.

 

Essential Reading / Recommended Reading

R1. Jayashree Suresh &B.S.Raghavan “Human values and Professional Ethics”, S. Chand, 2009.

                                   

R2.  Govindarajan, Natarajan and Senthilkumar “Engineering Ethics”, PHI:009.

                                               

R3.  Nagarajan “A Text Book on Professional ethics and Human values”, New Age International, 2009.

                                               

R4.  Charles &Fleddermann “Engineering Ethics”, Pearson, 2009.

                                               

R5.  Rachana Singh Puri and Arvind Viswanathan, I.K.”Practical Approach to Intellectual Property rights”, International Publishing House, New Delhi. 2010.

                                               

R6.  A.B.Rao “Business Ethics and Professional Values”, Excel, 2009

Evaluation Pattern

CIA I -Evaluated out of (20) --> CIA I cnverted to (10)

CIA II - Evaluated out of (50) ---> CIA II cnverted to ( 25) 

CIA III - Evaluated out of (20) ----> CIA III cnverted to (10)

Total CIA is scaled down to 20

Att. Marks5

ESE Evaluated out of (50) ---> ESE converted to (25) 

Total marks - 50

MA431 - PROBABILITY AND QUEUING THEORY (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

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. 

Course Outcome

CO1: Differentiate the continuous and discrete probability distributions and estimate the probability for the different parameter for the data. {L2} {PO1, PO2, PO3}

CO2: Distinguish different standard distributions like Binomial, Poisson, Uniform, and Normal, gamma, Weibull etc. and able to estimate the probability with proper examples. {L4} {PO1, PO2, PO3}

CO3: Interpret the data with the aid of Covariance Correlation and regression for two-dimensional random variable. {L3} {PO1, PO2, PO3}

CO4: Classify different random processes such as Stationary process, Markov process, Poisson process, Birth and death process, Markov chains, and explain transition probabilities - limiting distributions with examples. {L4} {PO1, PO2, PO3}

CO5: Construct the different Queuing models to find the number of customers in the system, waiting time etc. {L3} {PO1, PO2, PO3}

Unit-1
Teaching Hours:9
Probability and Random Variable
 

Axioms of probability - Conditional probability,  Random variable - Probability mass function - Probability density function  - Properties. Mathematical Expectation and Moments Relation between central and Non-central moments.

Unit-2
Teaching Hours:9
Standard Distributions
 

Binomial, Poisson, Geometric, Negative Binomial, Uniform, Exponential, Gamma, Weibull and Normal distributions and their properties-Functions of a random variable. Moment generating functions and their properties.

Unit-3
Teaching Hours:9
Two Dimensional Random Variables
 

Joint distributions - Marginal and conditional distributions – Covariance –Correlation and regression - Transformation of random variables – Central limit theorem.

Unit-4
Teaching Hours:9
Random Processes and Markov Chains
 

Classification - Stationary process - Markov process - Poisson process - Birth and death process - Markov chains - Transition probabilities - Limiting distributions. Transition Diagram.

Unit-5
Teaching Hours:9
Queuing Theory
 

Markovian models – M/M/1, M/M/C , finite and infinite capacity - M/M/∞ queues - Finite source model -  M/G/1 queue (steady state solutions only) – Pollaczek – Khintchine formula – Special cases.Single and Multiple Server System.

Text Books And Reference Books:

Text Books:

 

T1.  Ross, S., “A first course in probability”, 9th Edition, Pearson Education, Delhi,  2012.

T2.  Medhi J., “Stochastic Processes”, 3rd Edition, New Age Publishers, New Delhi, Reprint 2014. (Chapters 2, 3, & 4)

T3. T.Veerarajan, “Probability, Statistics and Random process”, 3rd Edition, Tata McGraw Hill, New Delhi,  2008.

 

Essential Reading / Recommended Reading

Reference Books:

R1. Allen., A.O., “Probability, Statistics and Queuing Theory”, Academic press, New Delhi, 1981.

R2. Taha, H. A., “Operations Research-An Introduction”, Seventh Edition, Pearson      Education Edition Asia, Delhi, 2002.

R3. Gross, D. and Harris, C.M., “Fundamentals of Queuing theory”, John Wiley and Sons, Second Edition, New York, 1985.

Evaluation Pattern

Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks)

End Semester Examination(ESE)      : 50% (50 marks out of 100 marks) 

  

S.No

Assessment

Marks

Weightagemarks

1

CIA I

20

10

2

CIA II

     (MSE: Mid Semester Examination)

50

25

3

CIA III

20

10

4

Attendance

10

05

5

ESE

(End Semester Examination)

100

50

Total

100

Components of the CIA

CIA I  :  Subject Assignments / Online Tests                  : 10 marks

CIA II :   Mid Semester Examination (Theory)                : 25 marks            

CIAIII: Quiz/Seminar/Innovative Assignments/presentations/publications : 10 marks

Attendance                                                                           : 05 marks

            Total                                                                                       : 50 marks

Mid Semester Examination (MSE) : Theory Papers:

  • The MSE is conducted for 50 marks of 2 hours duration.
  • Question paper pattern; Four questions have to be answered in part A without any choice. One question need to be answered out of two in part B. Each  question carries 10 marks

End Semester Examination (ESE):

The ESE is conducted for 100 marks of 3 hours duration.

The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.

Question paper pattern is as follows.

Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

The criteria for drawing the questions from the Question Bank are as follows

50 % - Medium Level questions

25 % - Simple level questions

25 % - Complex level questions

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

 

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

Course Outcome

CO1: Outline the basic concepts of reference models and the functionalities of physical layer in computer communications.

CO2: Experiment with the data link layer protocols for error detection and corrections mechanism.

CO3: Develop subnetting using IP addressing schemes and experiment with routing algorithms.

CO4: Analyze the functionalities and features used in UDP and TCP protocols.

CO5: Examine the Application layer protocols and cryptographic algorithms used in networking environment.

Unit-1
Teaching Hours:9
DATA COMMUNICATIONS
 

Introduction- Data communications: Components - Data Flow – Networks – Physical Structures – Network Types – Protocol Layering – TCP/IP Protocol Suite – OSI Model. Data and Signals –Digital Signals- Data Rate Limits- Performance- Digital Transmission – Digital to Digital Conversion- Line coding -Line coding Schemes –Transmission Media

Unit-2
Teaching Hours:9
DATA LINK LAYER
 

Introduction – Link Layer Addressing – Error Detection and Correction-Cyclic Codes- Check sum- Forward Error correction –Data Link Layer Protocols- Automatic Repeat (ARQ) protocols -Stop and Wait, Go-back-N, Selective Repeat, HDLC, PPP

Medium Access Control - Random Access Protocols -CSMA/CD, CSMA/CA, Channelization -FDMA-TDMA-CDMA, Wired LANs: IEEE Project 802.3, IEEE 802.4 - IEEE 802.5,  Wireless LAN- IEEE Project 802.11, WiMAX -IEEE Project 802.16.

 

Unit-3
Teaching Hours:9
NETWORK LAYER
 

Introduction – Network-Layer Services– Packet Switching– Network-Layer Performance– IPv4 Addresses – Internet Protocol (IP)-IPV4 , ICMP V4, ARP, IPv6 , Subnetting 

Routing-Introduction - Routing Algorithms- Distance Vector Routing, Link State Routing, Path Vector Routing, Unicast Routing Protocols- RIP, OSPF, BGP -NAT

 

Unit-4
Teaching Hours:9
TRANSPORT LAYER
 

Transport Layer Protocols- UDP -Introduction – Services, Port Numbers, User Datagram Protocol- User Datagram, UDP Services, UDP Applications

Transport Layer Protocols- TCP -Transmission Control Protocol- TCP Services, TCP features- TCP Connection- TCP Congestion control 

SCTP – SCTP Services, SCTP Features , Packet Format, Flow Control To Improve Qos.

 

Unit-5
Teaching Hours:9
APPLICATION LAYER
 

Application Layer -Introduction – DNS- SMTP- DHCP- FTP- HTTP-Telnet

Cryptography and Network Security-  Security Goals- Attacks- Confidentiality - Concepts of symmetric and asymmetric key cryptography-RSA, Sharing of symmetric keys - Diffie Hellman - Firewalls. 

Foundations of Modern Networking-Introduction: Software Defined Networking -SDN Architecture, Virtualization, The Internet of Things- Components

 

Text Books And Reference Books:

T1: Behrouz A. Forouzan, “Data communication and Networking with TCP/IP protocol suite”, Tata McGraw-Hill, Sixth Edition, 2021. ISBN 978-1-26-436335-3.

Essential Reading / Recommended Reading

R1: James F. Kurose, Keith Ross, “Computer Networking: A Top-Down Approach Featuring the Internet”, Pearson Education, 2020. ISBN: 9780135928523.

R2: Larry L. Peterson, Bruce S. Davie, Computer Networks: A Systems Approach Edition: 6th Edition, MK-Morgan Kaufmann/Elsevier-2021. ISBN: 978-0-12-818200-0.

R3: Andrew S. Tanenbaum, Nick Feamster, David J. Wetherall, Computer Networks: 6th Edition, Pearson, 2021, ISBN 9780136764052.

Evaluation Pattern

Continous internal assesment 70%

End Semester Examination 30%

CS532 - INTRODUCTION TO ARTIFICIAL INTELLIGENCE (2021 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

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.

Course Outcome

CO1: Illustrate the basics of Artificial Intelligence and problem solving.

CO2: Explain the various Searching Techniques.

CO3: Outline the Adversial Search and CSP.

CO4: Make use of Knowledge Engineering in real world representation.

CO5: Apply the different Forms of Learning.

Unit-1
Teaching Hours:9
INTRODUCTION
 

History - Applications  – Components of AI - Intelligent Agents - Characteristics of Intelligent Agents - Agents and Environments - Good behavior – The nature of environments – structure of agents - Problem Solving - problem solving agents – Example problems– Searching for solutions.

Unit-2
Teaching Hours:9
SEARCHING TECHNIQUES
 

Classical Search: Uniformed Search strategies - BFS - DFS- Bidirectional Search- Informed Heuristics Search Strategies -Heuristic function - Greedy - best -first search- A* Algorithm. local search algorithms and optimization problems –Hill-climbing Search, Simulated annealing, Local beam Search, Genetic algorithm -Searching with partial observations - Online Search Agents and Unknown Environment

Unit-3
Teaching Hours:9
GAME PLAYING and CSP
 

Games – Optimal decisions in games –Min-Max algorithm- Alpha – Beta Pruning – imperfect real-time decision –Stochastic Games.

Constraint Satisfaction Problem (CSP): Definition - Constraint propogation - Backtracking search - Local Search -The Structure of problems.

Unit-4
Teaching Hours:9
KNOWLEDGE REPRESENTATION
 

Logic - Propositional logic - First order logic –  Syntax and semantics for first order logic – Using first order logic – Knowledge engineering in first order logic. 

Inference in First order logic – propositional versus first order logic – unification and lifting – forward chaining – backward chaining - Resolution - Knowledge representation - Ontological Engineering - Categories and objects

 

Unit-5
Teaching Hours:9
LEARNING
 

Learning from Examples : Forms of Learning - Supervised learning - Learning Decision Trees - Regression and  classification with linear models, Artificial Neural Network. 

Knowledge in Learning : Logical formulation of learning – Explanation based learning – Learning using relevant information – Inductive logic programming. Statistical learning- Learning with complete data - Learning with hidden variable

Text Books And Reference Books:

T1. Stuart Russell and Peter Norvig, “Artificial Intelligence – A Modern Approach”, 4th Edition, Pearson Education, 2020.

T2.  Elaine Rich; Kevin Knight; Shivashankar B Nair, “Artificial Intelligence”, 3rd Edition, Tata McGraw-Hill, 2019.

T3. Francois Chollet “Deep Learning with Python”, 1st Edition Manning Publication, 2018

 

Essential Reading / Recommended Reading

R1. Jeff Heaton, "Artificial Intelligence for Humans, Volume 1: Fundamental Algorithms",1st edition,  ‎ CreateSpace Independent Publishing Platform, 2013

R2. George F. Luger, " Artificial Intelligence: Structures and Strategies for Complex Problem Solving", 6th Edition,  ‎ Pearson Education,2021

R3.Kevin Warwick, " Artificial Intelligence: The Basics",  ‎ Routledge, 2011

NPTEL Course:

1. Artificial Intelligence : Search Methods For Problem Solving By Prof. Deepak Khemani   |   IIT Madras

2. Fundamentals Of Artificial Intelligence By Prof. Shyamanta M. Hazarika   |   IIT Guwahati

Evaluation Pattern

1. Continuous Internal Assessment (CIA) for Theory 50% (50 marks out of 100 marks).

2. End Semester Examination (ESE): 50% (50 marks out of 100 marks).

CS533P - DESIGN AND ANALYSIS OF ALGORITHMS (2021 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

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.

Course Outcome

CO1: Demonstrate the process of algorithmic problem solving with time and space complexity.

CO2: Identify algorithm design techniques for searching and sorting.

CO3: Inspect algorithms under divide and conquer technique.

CO4: Solve problems by applying dynamic programming technique and determine the efficiency of algorithms.

CO5: Interpret the limitations of algorithm power and demonstrate backtracking technique.

Unit-1
Teaching Hours:9
INTRODUCTION AND FUNDAMENTALS OF THE ANALYSIS OF ALGORITHM EFFICIENCY
 

Introduction, Notion of Algorithm, Fundamentals of Algorithmic Solving, Important Problem Types, Fundamentals of the Analysis Framework, Mathematical Analysis  of Non-recursive Algorithm, Mathematical Analysis of Recursive Algorithm and examples, Empirical Analysis of Algorithms and Algorithm Visualization.

Unit-2
Teaching Hours:9
ALGORITHM DESIGN TECHNIQUES
 

Brute Force and Exhaustive Search: Selection Sort, Bubble Sort, Sequential Search and Brute-force string matching, Travelling Salesman Problem, Knapsack Problem, Assignment Problem. 

Decrease and Conquer: Insertion Sort and Topological Sorting and Fake Coin Problem, Russian Peasant Multiplication, Josephus Problem

Unit-3
Teaching Hours:9
ALGORITHM DESIGN TECHNIQUES
 

Divide and conquer: Merge sort, Quick Sort, Binary Tree Traversals and Related Properties and Multiplication of Large Integers and Strassen’s Matrix Multiplication.

Transform and Conquer: Presorting, Notion of Heap and Heapsort, Horner’s Rule and Binary Exponentiation.

Unit-4
Teaching Hours:9
ALGORITHM DESIGN TECHNIQUES
 

Space and Time Trade - Offs: Sorting by Counting, Horspool’s and Boyer - Moore Algorithm for String Matching, Hashing.

Dynamic Programming: Knapsack Problem, Warshall’s and Floyd’s Algorithm. 

Greedy Techniques: Prim’s Algorithm, Kruskal’s Algorithm, Dijkstra’s Algorithm.

Unit-5
Teaching Hours:9
ALGORITHM DESIGN TECHNIQUES
 

Limitations of Algorithm Power: Decision Trees, P, NP and NP Complete Problems, Challenges in Numerical Algorithms.

Backtracking: n-Queen’s Problem, Hamiltonian Circuit problem and Subset-Sum problem.

Branch and Bound: Assignment problem, Knapsack problem and Traveling salesman problem.

Text Books And Reference Books:
  1. AnanyLevitin, “Introduction to the Design and Analysis of Algorithm”, 3/e, Pearson Education Asia, Reprint 2012.
  2. Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser, “Data Structures and Algorithms in Java”, 6/e, Wiley, 2014.
  3. T. H Cormen, C E Leiserson, R L Rivest and C Stein: “Introduction to Algorithms”, 3rd Edition, The MIT Press, 2014.
Essential Reading / Recommended Reading
  1. Ellis Horowitz, Sartaj Sahni and Sanguthevar Rajasekaran, Computer Algorithms, Second Edition, Universities Press, 2007.
  2. Richard Neapolitan, “Foundations of Algorithms”, 5/e, Jones & Bartlett Learning, 2014.
  3. Richard Johnsonbaugh, Marcus Schaefer, “Algorithms”, Pearson Education, 2009.
  4. Clifford A Shaffer, “Data Structures and Algorithm Analysis in Java”, 3rd Edition, Courier Corporation, 2014.
Evaluation Pattern
  1. Continuous Internal Assessment (CIA) for Theory + Practical papers: 70% (70 marks out of 100 marks)
  2. End Semester Examination (ESE): 30% (30 marks out of 100 marks)

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

 

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.

Course Outcome

Unit-1
Teaching Hours:9
Introduction
 

A survey of Computer Graphics, Video Display Devices, Raster-Scan Systems, Graphics Workstation and Viewing Systems, Input Devices, Hard-Copy Devices, Graphics Networks, Graphics on the Internet.

Unit-2
Teaching Hours:9
Output primitives & 2-D, 3-D Geometrical transforms
 

Line Drawing Algorithms, DDA Algorithms, Bresenham's Line Algorithm, Circle-Generating Algorithms, Midpoint Circle Algorithms, Ellipse Algorithms, Basic Two-Dimensional Transformations, Matrix Representation, Three-Dimensional Translation, Three-Dimensional Rotation, Three-Dimensional Scaling, Other Three-Dimensional Transformations - Reflection and Shears.

Unit-3
Teaching Hours:9
Graphics in 2D with OpenGL
 

Java Graphics in 2D, Two-Dimensional Graphics in Java, Transformations and Modeling, Basics of OpenGL and JOGL, Basic OpenGL 2D Programs, Into the Third Dimension, Drawing in 3D, Normal and Textures

Unit-4
Teaching Hours:9
3D viewing & Projections
 

Projections ,Light & Material with Open GL Viewing and Projections, Perspective Projection, Orthographic Projection,  Light and Material, Vision and Color, OpenGL Materials, OpenGL Lighting, Lights and Materials in Scenes, Textures, Texture targets, Mipmaps and Filtering, Texture Transformations, Creating Texture with OpenGL, Loading Data into Texture, Texture Coordinate Generation

Unit-5
Teaching Hours:9
Introduction to Unreal Engine
 

Light and Material, Vision and Color, OpenGL Materials, OpenGL Lighting, Lights and Materials in Scenes, Case Study: Textures, Texture targets, Mipmaps and Filtering, Texture Transformations, Creating Texture with OpenGL, Loading Data into Texture, Texture Coordinate Generation, Texture Objects

Text Books And Reference Books:
  1. David J. Eck, “Fundamentals of Computer Graphics with Java, OpenGL and JOGL”, Hobart and Williams Smith colleges, 2010.
  2. Donald Hearn, Pauline Baker and Warren Carithers, “Computer Graphics with OpenGL”, 4th Edition Pearson, 2010.
  3. Dave Shreiner, Graham Sellers, John Kessenich, Bill Licea-Kane, "OpenGLR Programming Guide", Pearson Education, 2013
Essential Reading / Recommended Reading
  1. Donald Hearn and M.Pauline Baker, “Computer Graphics C Version”, Pearson Education, 2003.
  2. Foley, Vandam, Feiner and Huges, “Computer Graphics: Principles & Practice”, second edition, Pearson Education, 2003.
Evaluation Pattern

Weightage for CIA: 50

Weightage for ESE: 50

CS541E02 - INTERNET AND WEB PROGRAMMING (2021 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

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.

Course Outcome

CO1: .

Unit-1
Teaching Hours:9
HTML5 and CSS3
 

 HTML5:

 

Introduction to HTML5 basic tags, Forms, Multimedia (video, audio) markup and APIs, Canvas, Data Storage, Drag & Drop, Messaging & Workers CSS3:

Understanding basic CSS Syntax and Styles, Understanding Display, Position, and Document Flow, Changing and styling fonts, Adding transitions and animations, Introduction to usage of bootstrap and sass.

Unit-2
Teaching Hours:12
Java Script
 

Java Script: Introduction, Java script function’s, methods and objects, Decisions and loops, Document Object, Model (DOM), JavaScript Events, Ajax and JSON, API, error handling and debugging, Filtering and Form enhancement, Introduction to Dynamic Web Programming, Implementing jQuery and JavaScript in Web Pages, Building Richly Interactive Web Pages with jQuery, Introducing jQuery UI, Getting started and building Web applications with angular JS.

Unit-3
Teaching Hours:6
React JS
 

React js: Introduction, JSX in Depth, Data Flow and Life Cycle Events, Composite and Dynamic Components and Forms, Mixins and the DOM, React on the Server, React Addons, Performance of React Apps, React Router and Data Models, Animation, React Tools, Flux, Redux and React.

Unit-4
Teaching Hours:9
PHP
 

 Introduction to Server-Side Development with PHP, What is Server-Side Development, A Web Server’s Responsibilities, Quick Tour of PHP, Program Control, Functions, PHP Arrays and Super globals, Arrays, $_GET and $_POST Super global Arrays, $_SERVER Array, $_Files Array, Reading/Writing Files, PHP Classes and Objects, Object-Oriented Overview, Classes and Objects in PHP, Object Oriented Design, Error Handling and Validation, What are Errors and Exceptions?, PHP Error Reporting, PHP Error and Exception Handling, connectivity to database and processing the form.

Unit-5
Teaching Hours:9
CASE STUDY - Node.js
 

The Node Module System, The Node Programming Model, Events and Timers, The Command Line Interface, The File System, Streams, Binary Data, Executing Code, Network Programming, HTTP.

Node JS Database Connectivity, MVC Framework and Architecture, Web Hosting and Content Management System, Usage of Amazon storage for web application.

Text Books And Reference Books:

TEXT BOOKS:

1.      Bruce Lawson, Remy Sharp, “Introducing HTML 5”, Pearson Education, 2011.

2.      Ian Lunn, “CSS3 Foundations”, Wiley Publishers, 2012.

3.      Jon Duckett, “JavaScript and JQuery: Interactive Front-End Web Development”, Wiley Publishers: 2014.

4.      Sams, “Teach Yourself AngularJS, JavaScript, and jQuery All in One”, Pearson Education ,2015.

5.      Vipul A M, Prathomesh Sonpatki, “React JS by Example-Building Modern Web Application with React”, Packt Publishing,2019.

6.      Colin J. Ihrig, “Pro Node.js for Developers”, APRESS, 2013.

7.   Randy Connolly, Ricardo Hoar, "Fundamentals of Web Development”, 1 stEdition, Pearson Education India. (ISBN:978-9332575271)

 


Essential Reading / Recommended Reading

REFERENCE BOOKS:

1.      Matt West, “HTML5 Foundations”, Wiley Publishers: 2012.

2.      Training Guide Programming in HTML5 with JavaScript and CSS3 (MCSD) (Microsoft Press Training Guide), 2013.

3.      Elizabeth Castro, Bruce Hyslop, “HTML and CSS: Visual QuickStart Guide” 8th edition, 2013.

4.      Robin Nixon, “Learning PHP, MySQL &JavaScript with jQuery, CSS and HTML5”, 4 thEdition, O’Reilly Publications, 2015. (ISBN:978-9352130153) 2) Luke Welling, Laura Thomson, “PHP and MySQL Web Development”, 5th Edition, Pearson Education, 2016. (ISBN:978-9332582736)

5.      Nicholas C Zakas, “Professional JavaScript for Web Developers”, 3rd Edition, Wrox/Wiley India, 2012. (ISBN:978-8126535088) 4) David Sawyer Mcfarland, “JavaScript & jQuery: The Missing Manual”, 1st Edition, O’Reilly/Shroff Publishers & Distributors Pvt Ltd, 2014 (ISBN:978- 9351108078)

6.       Zak Ruvalcaba Anne Boehm, “Murach's HTML5 and CSS3”, 3rdEdition, Murachs/Shroff Publishers & Distributors Pvt Ltd, 2016. (ISBN:978-9352133246)

Evaluation Pattern

 

Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks)

End Semester Examination (ESE): 50% (50 marks out of 100 marks)

 

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

 

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.

Course Outcome

CO1: Explain various features of Security mechanisms and services to study Standard Block Ciphers along with their design principles.

CO2: Utilize the basic concepts and algorithms of public key encryption mechanism for secure data transmission.

CO3: Compare various Cryptographic authentications protocols, Hash Functions, Algorithms and Standards.

CO4: Identify Various Protocols and Standards in Network Security.

CO5: Make use of various research directions at system level security.

Unit-1
Teaching Hours:9
Introduction
 

OSI Security Architecture, Classical Encryption techniques, Cipher Principles, DES, Crypto analysis of DES, AES, Block Cipher Design Principles and Modes of Operation, Triple DES, Placement of Encryption Function, Traffic Confidentiality.

Unit-2
Teaching Hours:9
Public Key Cryptography
 

Introduction to Number theory, Deffie Hellman Key Exchange, Key Management, Elliptic curve Cryptography, Confidentiality using Symmetric Encryption, Public Key Cryptography and RSA.

Unit-3
Teaching Hours:9
Authentication & Hash Functions
 

Authentication Requirements, Authentication Functions, Message Authentication Codes, Hash Functions, MD5, SHA, RIPEMD and HMAC Standards.

Unit-4
Teaching Hours:9
Network Security
 

Authentication Applications: Kerberos – X.509 Authentication Service – Electronic Mail Security – PGP – S/MIME - IP Security – Web Security.

Unit-5
Teaching Hours:9
Application Security
 

Intrusion detection – password management – Viruses and related Threats – Virus Counter measures – Firewall Design Principles – Trusted Systems, Secret sharing schemes, Probabilistic encryption, Quantum Encryption, Attribute and Identity Encryption CASE-Study.

Text Books And Reference Books:

1. William Stallings, “Cryptography and Network Security – Principles and Practices”, 6th Edition, 2016.

2. Bruce Schneier, “Applied Cryptography”, John Wiley & Sons Inc, 2015.

Essential Reading / Recommended Reading

AtulKahate, “Cryptography and Network Security”, Tata McGraw-Hill, 2013.           

2. Charles B. Pfleeger, Shari Lawrence Pfleeger, “Security in Computing”, Fifth Edition, Pearson Education, 2015.

Evaluation Pattern

CIA 50 Marks

ESE 50 Marks

CS581 - INTERNSHIP - I (2021 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:1

Course Objectives/Course Description

 

Internships are short-term work experiences that will allow  a student to observe and participate in professional work environments and explore how his interests relate to possible careers. They are important learning opportunities through industry exposure and practices.   

 Course Objectives: 

•Identify how the internship relates to their academic courses and preferred career path

•Integrate existing and new technical knowledge for industrial application

•Understand lifelong learning processes through critical reflection of internship experiences.

•Articulate their experience and skills to potential employers

Course Outcome

CO1: .

Unit-1
Teaching Hours:30
Regulations
 

1.The student shall undergo an Internship for30 days starting from the end of 4th semester examination and completing it during the initial period of 5th semester.

2.The department shall nominate a faculty as a mentor for a group of students to prepare and monitor the progress of  the students.

3. The students shall report the progress of the internship to the mentor/guide at regular intervals and may seek his/her advise.

4. The Internship evaluation will  be completed by the end of  5th semesters.

5. The students are permitted to carry out the internship outside India with the following conditions, the entire expenses are to be borne by the student and the University will not give any financial assistance.

6. Students can also undergo internships arranged by the department during vacation.

7. After completion of Internship, students shall submit a report to the department with the approval of both internal and external guides/mentors.

8. There will be an assessment for the internship for 1 credit, in the form of report assessment by the guide/mentor  and a presentation on the internship given to department constituted panel.

Text Books And Reference Books:

Nil

Essential Reading / Recommended Reading

Nil

Evaluation Pattern

Maximum Marks = 50(Only credit will be displayed in the score card)

Passing marks 40% min

Internship assessment will be carried out based on the following parameters, during the 5th semester as a single Presentation evaluation.

 

Total No. of Internship Hours
(5)

Learning Objectives
(10)

Performance
Contribution
(10)

Personal and
Professional
Development (10)

Quality of Study/work/paper (10)

Submission of Report (5)

Total
(50)

 

CSHO533AIP - ROBOTICS AND PROCESS AUTOMATION (2021 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

● To understand about RPA and its concepts

● Apply RPA tools and functionalities

● Understand the challenges and risks in RPA implementation

 

● Understand about bots and its usage in real time applications

Course Outcome

CO 1: Illustrate the advantages, techniques of RPA

CO 2: Illustrate control flow and decision making

CO 3: Experiment with automating desktop and web applications with exception handling

CO 4: Experiment with automating different files.

CO 5: Develop RPA projects.

Unit-1
Teaching Hours:9
INTRODUCTION
 

Introduction to RPA, what should be automated, what can be automated, Techniques of automation, Benefits of RPA, Components of RPA, RPA Platforms, Record and Play.

Unit-2
Teaching Hours:9
CONTROL FLOW AND DATA MANIPULATION
 

Variables: string variable, date time variable, number variable, Boolean variable; String Manipulation and List Variable; Data Table; Creating a first bot: working on a CSV file.

Unit-3
Teaching Hours:9
Unit III
 

Automating Web and Desktop applications; Interacting with active windows; Simulating keystroke and mouse activities; Triggers: Email trigger, Files and folder trigger, Hotkey trigger, Trigger loop; Exceptional Handling.

Unit-4
Teaching Hours:9
Unit 4
 

Working with Excel files; Working with PDF files; Automation using Email; Automation using word; Working with forms. Working with images.

Unit-5
Teaching Hours:9
Unit -V
 

RPA Challenge Website; Sales Order Processing; Using AI and RPA for Invoice Processing; Web Scrapping; Automated Customer Support Emails; Payroll Processing; Email Query Processing.

Text Books And Reference Books:

T1. Mullakara, Nandan, and Arun Kumar Asokan. Robotic process automation projects: Build real-world RPA solutions using UiPath and Automation Anywhere. Packt Publishing Ltd, 2020.

 

T2. Husan Mahey. Robotics and Process Automation with Automation Anywhere, Packt Publishing Ltd, 2020.

Essential Reading / Recommended Reading

NIL

Evaluation Pattern

CIA:70

ESE:30

CSHO533CSP - CYBER FORENSICS AND MALWARE DETECTION (2021 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

To analyze about best possible solutions for different vulnerabilities that are exploited for hacking

Course Outcome

CO1: To understand the fundamentals of Cyber forensic over different platforms.

CO2: To understand concepts of Malware Forensics; Web Attack Forensics; Bitcoin Forensics; Cyber Laws and Data Recovery & Analysis

CO3: To understand the nature of malware, its capabilities, and how it is combated through detection and classification

CO4: To apply the tools and methodologies used to perform static and dynamic analysis on unknown executables.

CO5: To understand the malware functionality and malware detection techniques

Unit-1
Teaching Hours:9
Unit-1
 

Introduction to Cyber Forensics; Windows Forensics; Linux Forensics, Mac OS Forensics; Anti-forensics; Network Forensics; Mobile Forensics; Cloud Forensics

Unit-2
Teaching Hours:9
UNIT-II
 

Malware Forensics; Web Attack Forensics; Emails and Email Crime, Bitcoin Forensics; Cyber Law and Cyberwarfare; Data Recovery & Data Analysis

Unit-3
Teaching Hours:9
UNIT-III
 

Introduction to malware, OS security concepts, malware threats, evolution of malware, malware types- viruses, worms, rootkits, Trojans, bots, spyware, adware, logic bombs, malware analysis, static malware analysis, dynamic malware analysis

Unit-4
Teaching Hours:9
UNIT-IV
 

STATIC ANALYSIS: Analyzing Windows programs, Anti-static analysis techniques- obfuscation, packing, metamorphism, polymorphism

DYNAMIC ANALYSIS: Live malware analysis, dead malware analysis, analyzing traces of malware- system-calls, api-calls, registries, network activities. Anti-dynamic analysis techniques-anti-vm, runtime-evasion techniques, Malware Sandbox, Monitoring with Process Monitor, Packet Sniffing with Wireshark, Kernel vs. User-Mode Debugging, OllyDbg, Breakpoints, Tracing, Exception Handling, Patching

Unit-5
Teaching Hours:9
UNIT-V
 

Malware Functionality: Downloader, Backdoors, Credential Stealers, Persistence Mechanisms, Privilege Escalation, Covert malware launching- Launchers, Process Injection, Process Replacement, Hook Injection, Detours, APC injection Malware Detection Techniques: Signature-based techniques: malware signatures, packed malware signature, metamorphic and polymorphic malware signature Non-signature based techniques: similarity-based techniques, machine-learning methods, invariant inferences

Text Books And Reference Books:

Text Books:

T1. Practical Cyber Forensics: An Incident-Based Approach to Forensic Investigations: Reddy, Niranjan, Published by Apress, Berkeley, CA, DOIhttps://doi.org/10.1007/978-1-4842-4460- 9, Print ISBN 978-1-4842-4459-3, 2019

T2. Practical malware analysis The Hands-On Guide to Dissecting Malicious Software by Michael Sikorski and Andrew Honig ISBN-10: 159327-290-1, ISBN-13: 978-1-59327-290-6, 2012

 

Essential Reading / Recommended Reading

Reference Books:

R1. Malware Detection A Complete Guide - 2019 Edition, Gerardus Blokdyk, Published by 5STARCooks, 2019, ISBN: 0655900845, 9780655900849

Evaluation Pattern

CIA 70%

ESE 30%

CSHO534AIP - COMPUTER VISION (2021 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

·        To provide an introduction to concepts in Computer Vision including fundamental Image Processing Operations, Image enhancement, edge detection, Texture, boundary, shape and motion analysis, object segmentation, image transformation and 3D vision.

   To provide practical experience in implementing Computer Vision algorithms.

Course Outcome

CO1: Experiment with basic image processing operations ? filtering, Morphology and thresholding.

CO2: Develop programs for the detection of edges, corners, points of interest and for texture analysis

CO3: Experiment with shape analysis algorithms.

CO4: Apply object segmentation and shape modelling for object detection and extraction.

CO5: Construct Computer Vision solution for a given problem

Unit-1
Teaching Hours:9
Unit-1
 

Images and imaging operations –   Image filtering and morphology  –   Thresholding.

Unit-2
Teaching Hours:9
Unit-2
 

Edge detection, Corner, interest point, and invariant feature detection – Texture analysis

Unit-3
Teaching Hours:9
Unit-3
 

Binary shape analysis – Boundary pattern analysis –Line, Circle, and Ellipse detection – generalized Hough transform

Unit-4
Teaching Hours:9
Unit-4
 

Object Segmentation and shape models - The three Dimensional world – Perspective n-point problem – invariants and perspective  

Unit-5
Teaching Hours:9
Unit-5
 

Image transformation and camera calibration – Motion. Case studies – Face detection and recognition, surveillance , In-vehicle vision systems

Text Books And Reference Books:

T1. E.R. Davies, Computer Vision: Principles, Algorithms, Applications, Learning, 5e, AP, 2018

Essential Reading / Recommended Reading

R1. Ponce Jean & Forsyth David , Computer Vision: A Modern Approach, 2e, Pearson, 2015

R2. Richard Szeliski, Computer vision: Algorithms and Applications, 1e, Springer, 2010

R3. J. R. Parker, Algorithms for Image Processing and Computer Vision, 2e, Wiley, 2010

Evaluation Pattern

CIA -70 Marks

ESE - 30 Marks

CSHO534CSP - INTRUSION DETECTION AND INCIDENT RESPONSE (2021 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

After learning the course for a semester, the student will be aware of the intrusion detections concepts in cyber-attacks and its corresponding preventions and incident responses to ensure the data is recovered in time and whole system is operational. The student would also get a clear idea on some of the cases with their analytical studies in IDS and Incident responses.

Course Outcome

CO 1: Explain the evolution from design protection to detection of intrusions

CO 2: Summarize the various intrusion detection system and its architectural models

CO 3: Identify the incident response when a computer intrusion occurs.

CO 4: Analyze the parameters needed to detect intrusions

CO 5: Evaluate the best practices that comprise intrusions with incident responses.

Unit-1
Teaching Hours:9
UNIT 1
 

Introduction to computer incident, legal environment, Network security and attacks, basics of incident detection, parameters for assessment of intrusion detection, Intrusion detection system and Detection approaches, Misuse detection, anomaly detection, specification based detection,  Hybrid detection and statistics

Unit-2
Teaching Hours:9
UNIT 2
 

Centralized, Distributed, Cooperative Intrusion Detection, Tiered architecture, Intrusion detection in security, Tool Selection and Acquisition Process, Bro Intrusion Detection, Prelude Intrusion Detection, Cisco Security IDS, Snorts Intrusion Detection, NFR security, Architecture models of IDs and IPs

Unit-3
Teaching Hours:9
UNIT 3
 

Basics of Incident Response, Preparing for Incident Response, Live Data Collection, Preparation, Identification, Containment, Eradication, Recovery

Unit-4
Teaching Hours:9
UNIT 4
 

Introduction to legal evidence preparation for incident response, Forensics Duplication, Network Surveillance/Evidence, statistical Analysis Investigating Windows, Investigating Unix, Malware Triage, ways of detecting residual after attacks

Unit-5
Teaching Hours:9
UNIT 5
 

Case studies: various intrusion scenarios and their incident response and evidence gathering along with possible solutions.

Text Books And Reference Books:
  1. Ali A. Ghorbani, Wei Lu, “Network Intrusion Detection and Prevention: Concepts and Techniques”, Springer, 2010
  2. Luttgens, Jason T., Matthew Pepe, and Kevin Mandia. Incident response & computer forensics. McGraw-Hill Education, 2014
Essential Reading / Recommended Reading
  1. Earl Carter, Jonathan Hogue, “Intrusion Prevention Fundamentals”, Pearson Education, 2006
  2. Casey, Eoghan. Digital evidence and computer crime: Forensic science, computers, and the internet. Academic press, 2011.
Evaluation Pattern

CIA 50 Marks

ESE 50 marks

ECOE5601 - EMBEDDED BOARDS FOR IOT APPLICATIONS (2021 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

The aim of this course is to introduce the architecture, programming and interfacing of peripheral devices with embedded boards for IOT applications and design IOT based smart applications.

Course Outcome

CO-1: Understand the architecture, programming and interfacing principles of ATMEGA32 AVR microcontroller and Rasberry P

Unit-1
Teaching Hours:9
NETWORKING SENSORS
 

Network Architecture - Sensor Network Scenarios- Optimization Goals and Figures of Merit- Physical Layer and Transceiver Design Considerations-MAC Protocols for Wireless Sensor Networks- Introduction of sensors and transducers.

Unit-2
Teaching Hours:9
ARDUINO BOARD AND its? INTERFACING
 

ATMEGA328 microcontroller - Architecture- memory organisation – Operating modes – On chip peripherals- Embedded communication interfaces-  Example programs using Arduino IDE- Integration of peripherals (Buttons & switches, digital inputs, Matrix keypad, Basic RGB color-mixing, electromechanical devices- Displays- sensors(Temperature, Pressure, Humidity, Water level etc.), camera, real time clock, relays, actuators, Bluetooth, Wi-fi).

Unit-3
Teaching Hours:9
IoT BASED SYSTEM DESIGN
 

Definition of IoT- Applications and Verticals- System Architecture-Typical Process Flows-Technological Enablers- Open Standard Reference Model- Design Constraints and Considerations- IoT Security-  Experiments using Arduino Platform

Unit-4
Teaching Hours:9
RASBERRY-PI
 

Introduction to Raspberry pi – configuration of Raspberry pi – programming raspberry pi - Implementation of IOT with Rasberry pi

Unit-5
Teaching Hours:9
IMPLEMENTATION
 

{This unit is entirely practical based}           

Implementation of a IOT based real time system. The concept of the specific embedded design has to be discussed. Eg: Smart Irrigation using IOT/ IoT Based Biometrics Implementation on Raspberry Pi/ Automation etc. Note: Unit – V will be based on a group project. Each group comprising of maximum 3 members. Any microcontroller can be used in Unit-V.

Text Books And Reference Books:

T1. Slama, Dirak “Enterprise IOT : Strategies and Best Practices for Connected Products and services”, Shroff Publisher, 1st edition, 2015

T2. Ali Mazidi, Sarmad Naimi, Sepehr Naimi “AVR Microcontroller and Embedded Systems: Using Assembly and C”, Pearson 2013

T3. Wentk, “Richard Raspberry Pi”, John Wiley & Sons, 2014

Essential Reading / Recommended Reading

R1. .K. Ray & K.M.Bhurchandi, “Advanced Microprocessors and peripherals- Architectures, Programming and Interfacing”, Tata McGraw Hill, 2002 reprint

R2. Gibson, “Microprocessor and Interfacing” Tata McGraw Hill,II edition, 2009

R3. Muhammad Ali Mazidi, Rolin D. Mckinlay, Danny Causey “8051 Microcontroller and Embedded Systems using Assembly and C” Prentice Hall of India, 2008

Evaluation Pattern

CIA 1, CIA 2, CIA 3, ESE (As per the university norms)

ECOE5602 - FUNDAMENTALS OF IMAGE PROCESSING (2021 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

The aim of this course is to introduce image processing fundamentals making the students to understand the different methods available to process an image and also give them an insight about the toolbox in MATLAB which can be used to do simulations in image processing. 

Course Outcome

CO1: Understand the basic principles of image processing

CO2: Understand the tools used for image processing applications

CO3: Analyze the methods used for image preprocessing

CO4: Apply the compression techniques and analyze the results

CO5: Develop an image processing system for a given application

Unit-1
Teaching Hours:9
DIGITAL IMAGE FUNDAMENTALS
 

Concept of Digital Image, conversion of analog image to digital, General Applications of image processing, Fundamental Steps in Digital Image Processing. Components of an Image Processing System. Elements of Visual Perception. Light and the Electromagnetic Spectrum. Image Sensing and Acquisition. Image Sampling and Quantization

Unit-2
Teaching Hours:9
MATLAB USING IP TOOL BOX
 

Introduction to MATLAB, Introduction to IP Tool box, Exercises on image enhancement, image restoration, and image segmentation, Fourier Transform, Discrete Fourier Transform and Discrete Cosine Transform

Unit-3
Teaching Hours:9
IMAGE PROCESSING TECHNIQUES PART 1
 

Image Enhancement in the Spatial Domain: Some Basic Gray Level Transformations. Histogram Processing. Enhancement Using Arithmetic/Logic Operations. Basics of Spatial Filtering. Smoothing Spatial Filters. Sharpening Spatial Filters. Importance of Image Restoration, Model of the Image Degradation/Restoration Process. Noise Models. Filters for Image Restoration: Minimum Mean Square Error (Wiener) Filtering. Constrained Least Squares Filtering. Geometric Mean Filter

Unit-4
Teaching Hours:9
IMAGE PROCESSING TECHNIQUES PART 2
 

Image Compression: Fundamentals. Image Compression Models. Elements of Information Theory. Error-Free Compression. Lossy Compression. Image Compression Standards. Image Segmentation: Detection of Discontinuities. Edge Linking and Boundary Detection. Thresholding. Region-Based Segmentation. Segmentation by Morphological Watersheds

Unit-5
Teaching Hours:9
APPLICATION OF IMAGE PROCESSING
 

Applications of image processing in the field of Biomedical, Remote sensing, Machine vision, Pattern recognition, and Microscopic Imaging

Text Books And Reference Books:

T1.Gonzalez and woods, Digital Image Processing using MATLAB, PHI, 2005

Essential Reading / Recommended Reading

No reference books

 

Evaluation Pattern

Evaluation Pattern

 

·         Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks)

·         End Semester Examination(ESE)      : 50% (50 marks out of 100 marks)

Components of the CIA

CIA I   :  Subject Assignments / Online Tests                      : 10 marks

CIA II  :   Mid Semester Examination (Theory)                    : 25 marks                  

CIA III  : Quiz/Seminar/Case Studies/Project/

              Innovative Assignments/presentations/publications       : 10 marks

Attendance                                                                             : 05 marks

            Total                                                                                       : 50 marks

ECOE5603 - OBSERVING EARTH FROM SPACE (2021 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

The aim of this course is to understand the basics and applications of Satellite Remote Sensing, become familiar with the usage of active and Passive remote Sensing from space and explore the applications of Satellite Remote Sensing from Ecology to National Security. The course will include some simple python based Jupyter Notebooks and open-source Remote Sensing resources. The course will introduce students to a career in Satellite remote sensing

Course Outcome

CO1: Understand the basics and applications of Satellite Remote Sensing

CO2: Describe usage of Passive remote Sensing from space

CO3: Explain the applications of active remote sensing from space

CO4: Understand the applications of Satellite Remote Sensing in Agriculture, Forest Biomass Measurement, Security and Geodesy

CO5: Apply the fundamentals of satellite and remote sensing for hazardoues and disaster management uses.

Unit-1
Teaching Hours:9
BASICS Of SATELLITES AND SATELLITE IMAGERY
 

History of Satellites, Types and Classification of Satellites, Launching of Satellites, orbits, attitude and orbit control, Satellite imagery and basics of Satellite datasets, Satellite Imagery for UN SDG, Satellite data analysis

Unit-2
Teaching Hours:9
INTRODUCTION TO PASSIVE SATELLITE IMAGERY
 

Concept of Imaging Spectroscopy, Difference between multispectral and hyperspectral, Spectral features, Types of Spectrometer Sensors and missions,resolution,AI and ML in satellite image analysis, Introduction to python and Jupyter notebooks for satellite image analysis

Unit-3
Teaching Hours:9
INTRODUCTION TO ACTIVE SATELLITE IMAGERY
 

Active imaging technology, radar range equation and its Implications, using amplitude phase and polarity of returned signals to measure target parameters,scattering matrix and its decomposition, Introduction to EarthEngine and Sentinel Hub

Unit-4
Teaching Hours:9
LAND APPLICATIONS
 

Use of Satellite Remote Sensing in Agriculture, Forest Biomass Measurement, Security and Geodesy

Unit-5
Teaching Hours:9
HAZARD AND DISASTER MANAGEMENT
 

Hazards and Disaster Management as per UN SDG, Use of Satellite Remote Sensing in predicting/monitoring floods, Earthquakes, volcanoes and Fires

Text Books And Reference Books:

T1. Rebekah B. Ismaili, “Earth Observation Using Python”, Wiley, 2021, Satellite Communication Anil Mainy Wiley 2010

T2. Ruiliang Pu, Hyperspectral Remote Sensing Fundamentals and Practice ,CRC Press 2017

T3. The SAR Handbook. NASA & Servir Global

T4. Liguo Wong,Chunhui Zhao,Hyperspectral Image Processing,Springer 2015

T5. Matteo Pastorino and Andrea Randazzo, “ Microwave Imaging Methods and Applications”, Artech House, 2018

Essential Reading / Recommended Reading

R1. Dimitri G. Manolakis  Hyperspectral Imaging Remote Sensing Physics, Sensors, and Algorithms,Cambridge University Press,2016

R2. Smith, B., Carpentier, M.H, “ The Microwave Engineering Handbook-Microwave systems and applications”, Springer

Evaluation Pattern

Evaluation Pattern

 

·         Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks)

·         End Semester Examination(ESE)      : 50% (50 marks out of 100 marks)

Components of the CIA

CIA I   :  Subject Assignments / Online Tests                      : 10 marks

CIA II  :   Mid Semester Examination (Theory)                    : 25 marks                  

CIA III  : Quiz/Seminar/Case Studies/Project/

              Innovative Assignments/presentations/publications       : 10 marks

Attendance                                                                             : 05 marks

            Total                                                                                       : 50 marks

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

 

This course introduces the fundamental concepts, principles, analysis and design of hybrid and electric vehicles.

Course Outcome

·         To understand concepts of hybrid and electric drive configuration, types of electric machines that can be used, suitable energy storage devices etc

·         To recognize the application of various drive components and selection of proper component for particular applications.

Unit-1
Teaching Hours:12
HYBRID VEHICLES
 

History and importance of hybrid and electric vehicles, impact of modern drive-trains on energy supplies. Basics of vehicle performance, vehicle power sources, transmission characteristics, and mathematical models to describe vehicle performance.

Unit-2
Teaching Hours:12
HYBRID TRACTION
 

Basic concept of hybrid traction, introduction to various hybrid drive-train topologies, power flow control in hybrid drive-train topologies, fuel efficiency analysis. Basic concepts of electric traction, introduction to various electric drive-train topologies, power flow control in hybrid drive-train topologies, fuel efficiency analysis.

Unit-3
Teaching Hours:12
MOTORS AND DRIVES
 

Introduction to electric components used in hybrid and electric vehicles, configuration and control of DC Motor drives, Configuration and control of Induction Motor drives, configuration and control of Permanent Magnet Motor drives, Configuration and control of Switch Reluctance Motor drives, drive system efficiency.

Unit-4
Teaching Hours:12
INTEGRATION OF SUBSYSTEMS
 

Matching the electric machine and the internal combustion engine (ICE), Sizing the propulsion motor, sizing the power electronics, selecting the energy storage technology, Communications, supporting subsystems

Unit-5
Teaching Hours:12
ENERGY MANAGEMENT STRATEGIES
 

Introduction to energy management strategies used in hybrid and electric vehicle, classification of different energy management strategies, comparison of different energy management strategies, implementation issues of energy strategies.

Text Books And Reference Books:

1.      BimalK. Bose, ‘Power Electronics and Motor drives’ , Elsevier, 2011

2.      IqbalHussain, ‘Electric and Hybrid Vehicles: Design Fundamentals’, 2nd edition, CRC Pr I Llc, 2010

Essential Reading / Recommended Reading

1.      Sira -Ramirez, R. Silva Ortigoza, ‘Control Design Techniques in Power Electronics Devices’, Springer, 2006

2.      Siew-Chong Tan, Yuk-Ming Lai, Chi Kong Tse, ‘Sliding mode control of switching Power Converters’, CRC Press, 2011

3.      Ion Boldea and S.A Nasar, ‘Electric drives’, CRC Press, 2005

Evaluation Pattern

CIA I - 20 marks

CIA II -midsem 50 marks

CIA III - 20 marks

ESE - 100 marks

EEOE532 - ROBOTICS AND AUTOMATION (2021 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:3

Course Objectives/Course Description

 

·         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.

Course Outcome

CO 1: To understand the basic concepts in robotics.

CO 2: To describe basic elements in a robotic system

CO 3: To understand the kinematics, dynamics and programming with respect to a robotic system.

CO 4: To understand the control system design for a robotic system

CO 5: To discuss some of the robotic applications

Unit-1
Teaching Hours:12
Introduction
 

Robot definitions - Laws of robotics - Robot anatomy - History - Human systems and Robotics - Specifications of Robots - Flexible automation versus Robotic technology - Classification applications

Unit-2
Teaching Hours:12
Robotic systems
 

Basic structure of a robot – Robot end effectors - Manipulators - Classification of robots – Accuracy - Resolution and repeatability of a robot - Drives and control systems – Mechanical components of robots – Sensors and vision systems - Transducers and sensors - Tactile sensors – Proximity sensors and range sensors - Vision systems - RTOS - PLCs - Power electronics

Unit-3
Teaching Hours:12
Robot kinematics, dynamics and programming
 

Matrix representation - Forward and reverse kinematics of three degree of freedom – Robot Arm – Homogeneous transformations – Inverse kinematics of Robot – Robo Arm dynamics - D-H representation of forward kinematic equations of robots - Trajectory planning and avoidance of obstacles - Path planning - Skew motion - Joint integrated motion – Straight line motion - Robot languages- Computer control and Robot programming/software

Unit-4
Teaching Hours:12
Control system design
 

Open loop and feedback control - General approach to control system design - Symbols and drawings - Schematic layout - Travel step diagram, circuit and control modes - Program control - Sequence control - Cascade method - Karnaugh-Veitch mapping - Microcontrollers - Neural network - Artificial Intelligence - Adaptive Control – Hybrid control

Unit-5
Teaching Hours:12
Robot applications
 

Material handling - Machine loading, Assembly, inspection, processing operations and service robots - Mobile Robots - Robot cell layouts - Robot programming languages

Text Books And Reference Books:

1.      Nagrath and Mittal, “Robotics and Control”, Tata McGraw-Hill, 2003.

2.      Spong and Vidhyasagar, “Robot Dynamics and Control”, John Wiley and sons, 2008.

3.      S. R. Deb and S. Deb, ‘Robotics Technology and Flexible Automation’, Tata McGraw Hill Education Pvt. Ltd, 2010.

Essential Reading / Recommended Reading

1.      Saeed B. Niku, ‘Introduction to Robotics’,Prentice Hall of India, 2003.

2.      Mikell P. Grooveret. al., "Industrial Robots - Technology, Programming and Applications",     McGraw Hill, New York, 2008.

Evaluation Pattern

CIA I -20 marks

CIA II - midsem 50 marks

CIA III - 20 marks

ESE - 100 marks

EEOE533 - SMART GRIDS (2021 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

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.

Course Outcome

CO1: Understand the difference between Smart Grid (SG) vs. Conventional power system (CPS).

CO2: Explore different types of technologies associated with SG and its operational management at consumer level.

CO3: Analyze different types of technologies associated with SG and its operational management at substation level.

CO4: Understand different information and communication technologies suitable for SG environment.

CO5: Understand different ways for handing power quality issues in SG environment at different stages.

Unit-1
Teaching Hours:9
INTRODUCTION TO SMART GRID
 

Evolution of Electric Grid, Concept of Smart Grid, Definitions, Need of Smart Grid, Functions of Smart Grid, Opportunities & Barriers of Smart Grid, Difference between conventional & smart grid, Concept of Resilient &Self Healing Grid, Present development & International policies in Smart Grid. Case study of Smart Grid.CDM opportunities in Smart Grid.

Unit-2
Teaching Hours:9
SMART GRID TECHNOLOGIES: PART 1
 

Introduction to Smart Meters, Real Time Prizing, Smart Appliances, Automatic Meter Reading(AMR), Outage Management System(OMS), Plug in Hybrid Electric Vehicles(PHEV), Vehicle to Grid, Smart Sensors, Home & Building Automation, Phase Shifting Transformers.

Unit-3
Teaching Hours:9
SMART GRID TECHNOLOGIES: PART 2
 

Smart Substations, Substation Automation, Feeder Automation. Geographic Information System(GIS), Intelligent Electronic Devices(IED) & their application for monitoring &protection, Smart storage like Battery, SMES, Pumped Hydro, Compressed Air Energy Storage, Wide Area Measurement System(WAMS), Phase Measurement Unit (PMU).

Unit-4
Teaching Hours:9
INFORMATION AND COMMUNICATION TECHNOLOGY FOR SMART GRID
 

Advanced Metering Infrastructure (AMI), Home Area Network (HAN), Neighborhood Area Network (NAN), Wide Area Network (WAN). Bluetooth, ZigBee, GPS, Wi-Fi, Wi-Max based communication, Wireless Mesh Network, Basics of CLOUD Computing & Cyber Security for Smart Grid. Broadband over Power line (BPL). IP based protocols.

Unit-5
Teaching Hours:9
POWER QUALITY MANAGEMENT IN SMART GRID
 

Power Quality & EMC in Smart Grid, Power Quality issues of Grid connected Renewable Energy Sources, Power Quality Conditioners for Smart Grid, Web based Power Quality monitoring, Power Quality Audit.

Text Books And Reference Books:

1. Ali Keyhani, Mohammad N. Marwali, Min Dai “Integration of Green and Renewable Energy in Electric Power Systems”, Wiley

2. Clark W. Gellings, “The Smart Grid: Enabling Energy Efficiency and Demand Response”,CRC Press

3. JanakaEkanayake, Nick Jenkins, KithsiriLiyanage, Jianzhong Wu, Akihiko Yokoyama,“Smart Grid: Technology and Applications”, Wiley

4. Jean Claude Sabonnadière, NouredineHadjsaïd, “Smart Grids”, Wiley Blackwell

5. Peter S. Fox Penner, “Smart Power: Climate Changes, the Smart Grid, and the Future ofElectric Utilities”, Island Press; 1 edition 8 Jun 2010

6. S. Chowdhury, S. P. Chowdhury, P. Crossley, “Microgrids and Active DistributionNetworks.” Institution of Engineering and Technology, 30 Jun 2009

7. Stuart Borlase, “Smart Grids (Power Engineering)”, CRC Press

Essential Reading / Recommended Reading

1. Andres Carvallo, John Cooper, “The Advanced Smart Grid: Edge Power DrivingSustainability: 1”, Artech House Publishers July 2011

2. James Northcote, Green, Robert G. Wilson “Control and Automation of Electric PowerDistribution Systems (Power Engineering)”, CRC Press

3. MladenKezunovic, Mark G. Adamiak, Alexander P. Apostolov, Jeffrey George Gilbert“Substation Automation (Power Electronics and Power Systems)”, Springer

4. R. C. Dugan, Mark F. McGranghan, Surya Santoso, H. Wayne Beaty, “Electrical PowerSystem Quality”, 2nd Edition, McGraw Hill Publication

5. Yang Xiao, “Communication and Networking in Smart Grids”, CRC Press.

Evaluation Pattern

Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks)

End Semester Examination(ESE)          : 50% (50 marks out of 100 marks)

Components of the CIA

CIA I  :  Subject Assignments / Online Tests             : 10 marks

CIA II:   Mid Semester Examination (Theory)                      : 25 marks                   

CIAIII: Quiz/Seminar/Case Studies/Project/

Innovative assignments/ presentations/ publications              : 10 marks

Attendance                                                                             : 05 marks

            Total                                                                            : 50 marks

Mid Semester Examination (MSE): Theory Papers:

The MSE is conducted for 50 marks of 2 hours duration.

Question paper pattern; Five out of Six questions have to be answered. Each question carries 10 marks

End Semester Examination (ESE):

The ESE is conducted for 100 marks of 3 hours duration.

The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.

Question paper pattern is as follows.

Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

The criteria for drawing the questions from the Question Bank are as follows

50 % - Medium Level questions

25 % - Simple level questions

25 % - Complex level questions

HS521 - PROJECT MANAGEMENT AND FINANCE (2021 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

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.

Course Outcome

CO1: Apply the concept of project management in engineering field through project management life cycle. {L2}{PO9,PO11}

CO2: Analyze the quality management and project activity in engineering field through work breakdown structure. {L2}{PO11}

CO3: Analyze the fundamentals of project and network diagram in engineering and management domain through PDM techniques. {L3}{PO11}

CO4: Understand the basics of Business finance and its applications. {L2}{PO11}

CO5: Understand the meaning and approached to Capital and Financial Structure. {L2}{PO11}

Unit-1
Teaching Hours:9
INTRODUCTION TO PROJECT MANAGEMENT
 

Introduction to Organisations, Principles of Management - its functions, Skills, Organisation Structure, Financial Feasibility. Introduction to Project, Concept, Project Management, Project Life Cycle, Role of Project Manager - Functional Areas, Qualities and Responsibilities, Impact of Delays in Project Completions.

Unit-2
Teaching Hours:9
PROJECT PLAN
 

Project management functions - Controlling, directing, project authority, responsibility, accountability, Scope of Planning, Market Analysis, Demand Forecasting, Product line analysis, Product Mix Analysis, New Product development, Plant location, plant capacity, Capital Budgeting, Time Value of Money, Cash flow importance, decision tree analysis.

Unit-3
Teaching Hours:9
PROJECT SCHEDULING
 

Introduction, Estimation of Time, Project Network Analysis - CPM and PERT model, Gantt Chart, Resource Loading,Resource Leveling, Resource Allocation.  Estimating activity time and total program time, total PERT/CPM planning crash times, software‘s used in project management.

Unit-4
Teaching Hours:9
PROJECT MONITORING AND CONTROLLING
 

Introduction, Purpose, Types of control, Designing and Monitoring Systems, reporting and types. Financial Control, Quality Control, Human Resource Control, Management Control System, Project Quality Management, Managing Risks.

Unit-5
Teaching Hours:9
PROJECT EVALUATION AND AUDITING
 

Types of Project Closures, Wrap-Up closure activities, Purpose of Project Evaluation - Advantages, factors considered for termination of project, Project Termination process, Project Final report. Budgeting, Cost estimation, cost escalation, life cycle cost. Project finance in the roads sector, Project finance (Build Own Operate (BOO) / Build Own Operate Transfer (BOOT) Projects / Build Operate and Transfer (BOT).

Text Books And Reference Books:

Text Books:

T1. “Effective Project Management”, Robert K. Wysocki, Robert Beck. Jr., and David B. Crane; - John Wiley & Sons 2003.

T2. . Richard A.Brealey, Stewart C.Myers, and Mohanthy, Principles of Corporate Finance, Tata McGraw Hill, 11th Edition, 2014.

Essential Reading / Recommended Reading

.

Evaluation Pattern

CIA - 50% out of 100

ESE - 50% out of 100

IC521 - CONSTITUTION OF INDIA (2021 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:0

Course Objectives/Course Description

 

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.

Course Outcome

CO1: Explain the fundamental rights granted to citizens of India as per the Constitution

CO2: Describe the Directive Principles of State Policy along with its key aspects

CO3: Explain the legislative powers of Union Government and its elected legislature

CO4: Understand the Indian judiciary with respect to civil and criminal aspects

CO5: Explain the working of state government and its electoral powers

Unit-1
Teaching Hours:6
Making of the Constitution and Fundamental Rights
 

Introduction to the constitution of India, the preamble of the constitution, Justice,  Liberty, equality, Fraternity, basic postulates of the preamble

Right to equality, Right to freedom, Right against exploitation, Right to freedom of religion, Cultural and educational rights, Right to constitutional remedies 

 

Unit-2
Teaching Hours:6
Directive Principles of State Policy and Fundamental Duties
 

Directive Principles of State Policy, key aspects envisaged through the directive principles, Article 51A and  main duties of a citizen in India

Unit-3
Teaching Hours:6
Union Government and Union Legislature
 

the president of India, the vice president of India, election method, term, removal, executive and legislative powers, prime minister and council of ministers, election, powers, parliament, the Upper House and the Lower House, composition, function

Unit-4
Teaching Hours:6
Indian Judiciary
 

Supreme court, high courts, hierarchy, jurisdiction, civil and criminal cases, judicial activism 

Unit-5
Teaching Hours:6
State Government and Elections in India
 

State executive, governor, powers , legislative council and assembly, composition, powers, electoral process, election commission, emergency

Text Books And Reference Books:

R1. B R Ambedkar, ‘The Constitution of India’. Government of India

R2. Durga Das Basu, Introduction to the Constitution of India, LexisNexis, 24th edition

Essential Reading / Recommended Reading

-

Evaluation Pattern

As per university norms

IT541E01 - UNIX AND SHELL PROGRAMMING (2021 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 
  • Identify and define key terms related to operating system.
  • Explain basic Unix concepts related to concurrency and control of programs.
  • Capability to name and state the function of Unix commands.

Course Outcome

CO1: .

Unit-1
Teaching Hours:9
INTRODUCTION
 

General Overview of the System: System structure, user perspective, O/S services assumption about Hardware, The Kernel and buffer cache architecture of Unix O/S, System concepts, Kernel data Structure, System administration, Buffer headers, Structure of the buffer pool, Scenarios for retrieval of the buffer, Reading and writing disk block, Advantage and disadvantage of buffer cache.

Unit-2
Teaching Hours:9
INTERNAL REPRESENTATION OF FILES
 

Internal Representation of Files: Inodes, Structure of regular, Directories conversions of a path name to an inode, Super block, Inode assignment to a new file, Allocation of disk blocks, Open read write file and record close, File creation, Operation of special files change directory and change root, change owner and change mode. STAT and FSTAT, PIPES mounting and unmounting files system, Link Unlink

Unit-3
Teaching Hours:9
STRUCTURES OF PROCESSES AND PROCESS CONTROL
 

Structures of Processes and process control: Process states and transitions layout of system memory, the context of a process, manipulation of process address space, Sleep process creation/termination. The user Id of a process, changing the size of a process. Killing process with signals, job control, scheduling commands: AT and BATCH, TIME, CORN.

Unit-4
Teaching Hours:9
INTRODUCTION TO SHELL SCRIPTS
 

Introduction to shell scripts: shell Bourne shell, C shell, Unix commands, permissions, editors, grep family, shell variables, scripts, metacharacters and environment, if and case statements, for while and until loops. Shell programming.

Unit-5
Teaching Hours:9
INTRODUCTION OF AWK AND PERL PROGRAMMING
 

Introduction of AWK and Perl Programming: AWK pattern scanning, BEGIN and END patterns, AWK arithmetic and variables, and operators, functions, perl; the chop() function, variable and operators. Networking tools: Resolving IP addressing, TELNET, FTP, Socket programming, introduction of Linux structure.

Text Books And Reference Books:

Text Books:

1. Sumitabha Das “Unix concepts and Applications”, Tata McGraw Hill, Fourth Edition, 2017.

2. Y.Kanetkar “Unix shell programming”, BPB Pub.

3. M.J. Bach “Design of UNIX O.S.", PHI Learning.

Essential Reading / Recommended Reading

Reference Books:

1. B.W. Kernighan & R. Pike, “The UNIX Programming Environment”, PHI Learning.

2. S.Prata “Advanced UNIX: A Programming's Guide”, BPB Publications, New Delhi.

3. Beck “Linux Kernel, Pearson Education, Asia.

Evaluation Pattern

CIA - 50% out of 100

ESE - 50% out of 100

NCCOE1 - NCC1 (2021 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

·       This Course is offered for cadets of NCC who have successfully completed their B- Certificate.

·       This Course is offered for the NCC cadets in the Open Elective course offered by the department during the 5th Semester.

·        This course can be selected if and only if the cadet Successfully Completes the ‘B’- Certificate exam that is conducted centrally oraganized by the NCC Directorate.

Course Outcome

CO1: .

Unit-1
Teaching Hours:9
Introduction to NCC
 

The NCC- Aims, Objectives and Org of NCC-Incentives-Duties of NCC Cadet- NCC Camps: Types and Conduct. National Integration- Importance and Necessity- Factors affecting National Integration- Unity in Diversity.

Unit-2
Teaching Hours:9
Drill
 

Fundamentals of Foot Drill- Word of Command-Sizing- Salute- Basic Movements – Marching.

Fundamentals of Rifle Drill - Basic Movements- Introduction to .22 Rifle- Handling of .22 Rifle- Range procedure and Theory of grouping.

Unit-3
Teaching Hours:9
Social Services
 

Social Services-Community Development - Swachh Bharat Abhiyan - Social Service Capsule- Basics of Social Service- Rural Development Programmes- NGO’s.

Unit-4
Teaching Hours:9
Personality Development
 

Factors in personality Development- Self-Awareness-Empathy - Critical and Creative Thinking - Decision Making and Problem Solving- Communication Skills- Public Speaking- Group Discussions.

Unit-5
Teaching Hours:9
Disaster Management, Health and Hygiene
 

Organization - Types of Disasters - Essential Services Assistance - Civil Defense Organization - Natural Disasters- Man Made Disasters- Firefighting -Hygiene and Sanitation (Personal and Camp)- First Aid in Common Medical Emergencies and Treatment of Wound.

Text Books And Reference Books:

1.Airwing Cadet Handbook, Specialized Subject SD/SW, Maxwell Press, 2016.

2. Airwing Cadet Handbook, Common Subject SD/SW, Maxwell Press, 2015.

Essential Reading / Recommended Reading

1.Airwing Cadet Handbook, Specialized Subject SD/SW, Maxwell Press, 2016.

2. Airwing Cadet Handbook, Common Subject SD/SW, Maxwell Press, 2015.

Evaluation Pattern

1. The assessment will be carried out as overall internal assessment at the end of the semester for 100 marks based on the following.

 

·       Each cadet will appear for ‘B’ Certificate exam which is centrally conducted by the Ministry of Defense, NCC directorate. The Total marks will be for 350.

·       Each cadets score will be normalized to a maximum of 100 marks based on the overall marks Secured by each cadet. 

VCSE514 - CCNA: INTRODUCTION TO NETWORKS (ITN) (2021 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:0

Course Objectives/Course Description

 

CCNAv7 teaches comprehensive networking concepts and skills, from network applications to the protocols and services provided to those applications. Learners will progress from basic networking to more complex enterprise and theoretical networking models later in the curriculum. 

The first course in the CCNA curriculum, Introduction to Networks (ITN) introduces the architectures, models, protocols, and networking elements that connect users, devices, applications and data through the internet and across modern computer networks - including IP addressing and Ethernet fundamentals.  

The second course, Switching, Routing and Wireless Essentials (SRWE) focuses on switching technologies and router operations that support small-to-medium business networks and includes wireless local area networks (WLANs) and security concepts.

Course Outcome

CO1: By the end of the course1, Introduction to Networks (ITN), students can build simple local area networks (LANs) that integrate IP addressing schemes, foundational network security, and perform basic configurations for routers and switches.

CO2: Students learn key switching and routing concepts. They can perform basic network configuration and troubleshooting, identify and mitigate LAN security threats, and configure and secure a basic WLAN.

Unit-1
Teaching Hours:30
CCNAv7: Introduction to Networks (ITN)
 

Networking Today, Basic Switch and End Device Configuration, Protocols and Models, Physical Layer, Number Systems, Data Link Layer, Ethernet Switching, Network Layer, Address Resolution, Basic Router Configuration, IPv4 Addressing, IPv6 Addressing, ICMP, Transport Layer, Application Layer, Network Security Fundamentals, Build a Small Network

Unit-2
Teaching Hours:30
CCNAv7: Switching, Routing and Wireless Essentials (SRWE)
 

Basic Device Configuration, Switching Concepts, VLANs, Inter-VLAN Routing, STP, EthercCannel, DHCPv4, SLAAC and DHCPv6 Concepts, FHRP Concepts, LAN Security Concepts, Switch Security Configuration, WLAN Concepts, WLAN Configuration, Routing Concepts, IP Static Routing, Troubleshoot Static and Default routes.

Text Books And Reference Books:

1. https://lms.netacad.com/course/view.php?id=2145156

2. https://lms.netacad.com/course/view.php?id=2144468

3. Introduction to Networks Companion Guide (CCNAv7), By Cisco Networking Academy, Pearson, 2020. 

4. Switching, Routing, and Wireless Essentials Companion Guide (CCNAv7), Cisco Press, Hoboken, New Jersey. 2020.

Essential Reading / Recommended Reading

1. Behrouz A. Forouzan, “Data communication and Networking”, Tata McGraw-Hill, 2013.

2. James F. Kurose and Keith W. Ross, “Computer Networking: A Top-Down Approach Featuring the Internet”, Pearson Education, 2012.

3. Larry L.Peterson and Peter S. Davie, “Computer Networks”, Fifth Edition, Harcourt Asia Pvt. Ltd., Second Edition, Publishers, 2012.            

4. Andrew S. Tanenbaum, “Computer Networks”, 5th Edition, Pearson 2012.

5. William Stallings, “Data and Computer Communication”, Sixth Edition, Pearson Education, 2007.

 

Evaluation Pattern

Online Assessments

VCSE516 - FULL STACK WEB DEVELOPMENT (2021 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:0

Course Objectives/Course Description

 

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

Course Outcome

-: By the end of the course, students can demonstrate a strong understanding of core Java concepts, including object-oriented programming, data types, variables, and control structures. Create responsive and interactive user interfaces using HTML, CSS, and JavaScript. Use front-end libraries and frameworks like React or Angular to build dynamic web pages. Build server-side applications using Java technologies such as Spring. Implement RESTful APIs for communication between the front-end and back-end components.

Unit-1
Teaching Hours:30
Core Java
 

Declaration and Access Control, Object Orientation, Operators, Interface, Maven Fundamentals, String, Generics and Collections, Stream API's, Layered Architecture.

Unit-2
Teaching Hours:30
Spring, Spring Boot and Angular
 

Spring Core Introduction / Overview, Spring Container, Dependency Injection, Metadata / Configuration, SPRING BOOT Introduction, Spring Data JPA, Spring Data REST. HTML5, CSS3, BootStrap, Introduction to Angular Framework, Essentials of Angular, Templates, Styles & Directives, Pipes, Services & Dependency Injection, Template-Driven and Reactive Forms, Components Deep Dive / Routing, Http Requests / Observables.

Text Books And Reference Books:
  1. Herbert Schildt, Java: The Complete Reference, 9th/12th Edition, 2021.
  2. Spring: https://spring.io or  https://spring.io/quickstart
  3. Angular: https://angular.io/docs

 

Essential Reading / Recommended Reading
  1. "Spring in Action" by Craig Walls - A comprehensive guide to the Spring Framework, one of the most widely used Java frameworks for building web applications.
  2. "Java Persistence with Hibernate" by Christian Bauer and Gavin King - Focuses on Java Persistence API (JPA) and Hibernate, a popular ORM (Object-Relational Mapping) framework.
Evaluation Pattern

Project

BTGE631 - CORPORATE SOCIAL RESPONSIBILITY (2021 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:100
Credits:2

Course Objectives/Course Description

 

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 

 

  • To understand the concept of CSR and the theoretical underpinnings.

  • To understand the stakeholder approaches.

  • To provide an experiential, integrative, substantive, and high quality experience surrounding issues of Corporate Social Responsibility

  • To provide participating students with a truly unique curriculum experience with field experience.

Course Outcome

CO1: The students will be able to demonstrate their understanding in general on CSR.

CO2: To exhibit their skill in executing the responsibilities and implementing different approaches in CSR.

CO3: The students will be able to critically evaluate the CSR programs of a corporate

Unit-1
Teaching Hours:7
Corporate social responsibility
 

Defining CSR. Aim and Objectives, Components of CSR, key  drivers,  History  and  Evolution  of  CSR  in  the  Indian and international  context,  CSR  policies  and  Governance,  Laws  and Regulations. Competencies of CSR Professionals. 

Unit-2
Teaching Hours:7
Stakeholder Engagement
 

Stakeholder engagement, Interaction in a Multi-Stakeholder Context: CSR role on internal environment: Employees, Human Resource Management - labour security and human rights, Health and Safety.CSR role on External environment: 1) Customers: Consumer rights and movements affecting CSR; (2) Community: Community involvement, (3) Shareholders (4) Suppliers.

Unit-3
Teaching Hours:6
CSR towards Environment and Biodiversity
 

Environment: Need for Environmental assessments. Governments’ response to CSR. Role of Biodiversity, Climate change and Environment in business. Environmental compliance. 

Unit-4
Teaching Hours:4
Sustainability models
 

Benefits of CSR to Business. Factors hindering CSR activities in companies

Unit-5
Teaching Hours:6
Theories of CSR
 

Theories of CSR: A.B Carroll, Wood, and stakeholders Theories.  The triple bottom line approach.  Stakeholder engagement, Standards and Codes – SA 8000, the Global Compact, GRI, ISO 26000.

Text Books And Reference Books:
  • Agarwal, S. (2008). Corporate social responsibility in India. Los Angeles: Response.

  • Visser, W. (2007). The A to Z of corporate social responsibility a complete reference guide to concepts, codes and organisations. Chichester, England: John Wiley & Sons. 

  •  Crane, A. (2008). Corporate social responsibility: Readings and cases in a global context. London: Routledge.

  •  Werther, W., & Chandler, D. (2006). Strategic corporate social responsibility: Stakeholders in a global environment. Thousand Oaks: SAGE Publications.
Essential Reading / Recommended Reading
  • Baxi, C. (2005). Corporate social responsibility: Concepts and cases: The Indian experience. New Delhi, India: Excel Books.

  • Visser, W. (2011). The age of responsibility CSR 2.0 and the new DNA of business. Chichester, West Sussex: John Wiley & Sons.
Evaluation Pattern

CIA 1 - 20 Marks

CIA 2 - 50 Marks 

CIA 3 - 20 marks

 

ESE - 100 marks

BTGE632 - DIGITAL MEDIA (2021 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:100
Credits:2

Course Objectives/Course Description

 

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.

Course Outcome

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.

Unit-1
Teaching Hours:10
Concepts
 

Website Hosting/Design/Development/Content, Fundamentals of SEO, Voice Search Optimization, Local SEO, Advanced/Technical SEO, SEO Audit, Competition Analysis, Concepts of Digital Marketing

Unit-2
Teaching Hours:10
Marketing
 

Marketing on platforms – Facebook/Twitter/LinkedIn/Instagram/YouTube, Quora, Basics of Video Editing, Inbound Marketing, Email Marketing, Digital Marketing Planning and Strategy, Marketing Automations and Tools

Unit-3
Teaching Hours:10
Growth Hacking
 

Ethical vs. Unethical, Funnels, KPI’s, Viral Coefficient, Cohorts, Segments, Multivariate Testing, Lifetime Value of a Customer, Customer Acquisition Cost, Analytics Types, Tools, Project

Text Books And Reference Books:

Phillip J. Windley, "Digital Identity" O'Reilly Media, 2005

Essential Reading / Recommended Reading

Dan Rayburn, Michael Hoch, "The Business of Streaming and Digital Media", Focal Press, 2005

Evaluation Pattern
  • CIA 1 - Evaluated out of 20, which will be converted to 10
  • CIA 2 - Mid Semester Exam evaluated out of 50, which will be converted to 25
  • CIA 3 - Evaluated out of 20, which will be converted to 10
  • Total CIA Marks after conversion - 45
  • Attendance Marks - 5
  • ESE Evaluated out of 100, which will be converted to 50
  • Total Marks = CIA (Total) + ESE + Attendance = 45 + 50 + 5 = 100

 

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

 

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

Course Outcome

1: Upon completing the syllabus students will be able to show a good grasp of the fundamentals of English language. Students will be able to deliver the topic orally and in writing with greater independence and greater linguistic correctness

2: Will be able to distinguish and discuss differences in English language structure between speech and writing as well as distinguish and discuss stylistic differences (formal and informal English)

3: Will be able to actively and independently participate in group discussions, can make successful attempt to persuade in decision making, and can withstand the pressures in interview.

4: Will be equipped to network in academic and work settings. Would be able to confidently appear in front of a larger crowd and give presentations

5: Will acquire skills in CV writing, cover letter writing and content generation

Unit-1
Teaching Hours:6
Verbal
 

       Training on Nouns, Pronouns, Homophones, Homonyms

       Verbs and Gender

       Training on Tenses

       Active Voice, Passive Voice and Sentence Formation

       Direct and Indirect Speech

       Adjectives and Adverbs

Unit-2
Teaching Hours:6
FORMAL COMMUNICATION
 

       Barriers of communication and effective solutions

       Workplace English

       Pleasantries and networking

       Cross-cultural understanding

 

Unit-3
Teaching Hours:6
WRITTEN Workplace English
 

•    Professional Writing

•    Analytical

•    Instructional including writing MOMs

•    Project Planning

•    Creative writing

•    Blogging

•    Event management proposal meeting

       •     Professional communication – Email Etiquette, Cover letters, Resume

Unit-4
Teaching Hours:6
WRITTEN Academic Writing
 

       Application in technical fields and written communication

       Project writing, essays and theories

       Paper presentation skills and creative writing

       Final project writing

Unit-5
Teaching Hours:6
PUBLIC SPEAKING
 

       Training on Presentation Skills

       Body Language and Accent Training

       Voice projection

       Group Discussion Do’s and Don’ts

       Getting individual feedback

Training on appropriate grooming code and body language in a professional workplace and delivery of apt elevator pitch

Text Books And Reference Books:

   TEXT BOOKS

       High School English Grammar and Composition Book, Wren and Martin

       Writing At Work: Professional Writing Skills for People, Edward L. Smith and Stephen A. Bernhardt

Essential Reading / Recommended Reading

REFERENCE BOOKS

       English grammar in use book – Raymond Murphy

       WordPress to Go: How to Build a WordPress Website on Your Own Domain, from Scratch, Even If You Are a Complete Beginner Sarah McHarry.

       The Art of Public Speaking

       Textbook by Stephen E. Lucas

      True Professionalism, David Maister

 

 

Evaluation Pattern

Stress Interview/ Panel Discussion/Group

BTGE634 - GERMAN (2021 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:100
Credits:2

Course Objectives/Course Description

 

 

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.

Course Outcome

CO1: Can understand and use familiar, everyday expressions and very simple sentences, which relate to the satisfying of concrete needs.

CO2: Can introduce oneself and others as well as ask others about themselves ? e.g. where they live, whom they know and what they own ? and can respond to questions of this nature.

C03: Can handle everyday situations like shopping, eating out, visiting places, travelling, holidaying, requesting for information, making an appointment, cancelling an appointment, filling up a form etc.

Unit-1
Teaching Hours:6
INTRODUCTION, SELF AND OTHERS
 

Introduction: Greeting and saying goodbye, Introducing yourself and others, Talking about yourself and others.

Numbers, telephone numbers and mail-addresses, the alphabet (spelling), countries and languages.

Question words, sentences, verbs and personal pronouns.

Unit-2
Teaching Hours:6
AROUND YOU? :FRIENDS, COLLEGEAUS
 

Hobbies, meeting friends, Weekdays, months and seasons, work and working times

Articles, verbs, Yes/ no questions, Plurals, The verbs “to have” and “to be”.

Unit-3
Teaching Hours:6
PLACES TO VISIT
 

Places in the city, asking for directions, Means of transport. Orientation in a city.

Imperative sentences.

Unit-4
Teaching Hours:6
FOOD
 

Shopping for food, conversation during food shopping, ordering food and drinks, general greetings during eating out.

Word position in sentence, accusative case.

Unit-5
Teaching Hours:6
TIME WITH FRIENDS
 

Telling time and organizing meetings with family and friends.

Making plans, Birthday invitations, in Restaurants.

Finding information in a text, event tips in the radio, leisure activities, brochures.

Possessive articles, Modal verbs ,simplePast tense (to have and to be)

Text Books And Reference Books:

·       Netzwerk – Deutsch als Fremdsprache A1.

Publisher- Langenscheidt

Essential Reading / Recommended Reading

·       Netzwerk – Deutsch als Fremdsprache A1.

Publisher- Langenscheidt

Evaluation Pattern

·       CIA I

 

Content

 

 

Marks

 

Nature of evaluation

 

Self introduction

Answering 2 Questions

 

 

4

6

 

Speaking

 

Filling an application form

 

 

10

 

Written

 

 

·       CIA II

Written examination 50 marks

 

·       CIA III

 

Content

 

 

Marks

 

Nature of evaluation

 

Hearing comprehension

Reading comprehension

 

 

5

5

 

Listening to a track

Written

 

Writing a letter

 

 

10

 

Written

·       SEMESTER EXAM

 

Written examination 100 marks

 

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

 

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.

 

Course Outcome

CO1: Understand the meaning and importance of intellectual property rights as well as different categories of intellectual property.

CO2: Understand the meaning of patentable invention, the procedure for filing patent applications, rights of the patentee and the different rights of patentee.

CO3: Maintain research records in the patent process, the process of patent document searching and how to interact with patent agent or attorney.

CO4: Understand the issues related to patenting of software, digital rights management and database management system.

CO5: Understand the intellectual property issues in e- commerce, evidentiary value of electronic signature certificates, protection of websites and the protection of semiconductor integrated circuits.

Unit-1
Teaching Hours:6
Introduction
 

Detailed Syllabus: Philosophy of intellectual property - Intellectual Property & Intellectual Assists – Significance of IP for Engineers and Scientists – Types of IP – Legal framework for Protection of IP – Strategies for IP protection and role of Engineers and Scientists.

Unit-2
Teaching Hours:6
Patenting Inventions
 

Meaning of Invention – Product and Process Patents – True inventor – Applications for Patent – Procedures for obtaining Patent – Award of Patent – rights of patentee – grounds for invalidation – Legal remedies – International patents

Unit-3
Teaching Hours:6
Inventive Activities
 

Research Records in the patent process – Inventorship - Internet patent document searching and interactions with an information specialist - Interactions with a patent agent or attorney - Ancillary patent activities - Technology transfer, patent licensing and related strategies.

Unit-4
Teaching Hours:6
Computer Implemented Inventions
 

Patents and software – Business Method Patents – Data protection – Administrative methods – Digital Rights Management (DRM) – Database and Database Management systems - Billing and payment – Graphical User Interface (GUI) – Simulations – E-learning – Medical informatics – Mathematical models

Unit-5
Teaching Hours:6
Innovations in E-Commerce
 

IP issues in e-commerce - Protection of websites – website hosting agreements – Copyright issues – Patentability of online business models – Jurisdiction – Digital signatures – Evidentiary value of Electronic signature certificates – Role of Certifying Authorities – Protection of  Semiconductor ICs

Text Books And Reference Books:

1. V.J. Taraporevala’s, Law of  Intellectual Property, Third Edition, 2019

2. Elizabeth Verkey, Intellectual Property, Eastern Book Company,  2015

Essential Reading / Recommended Reading

1. Martin Adelman, Cases and Materials on Patent Law, 2015

2. Avery N. Goldstein, Patent Law for Scientists and Engineers, Taylor & Francis (2005)

Evaluation Pattern

CIA 1

Assignment description: Class test to identify the different aspects of IP.

 

Assignment details: MCQs

 

CIA II (MSE)

Assessment Description: Closed book exam

Assignment Details: Mid semester examination five questions need to be answered.

 

CIA III

Assessment Description: Students would be assessed on the understanding of the different forms of IP, relevant theoretical justifications of intellectual property protection and the relevant IP statute from practitioner’s approach taught in the class and their ability to apply it correctly to the given problem and proposing solutions.

 

Assignment details: Students will be given a hypothetical legal problem in IP and will be required to write short essay, containing maximum 500 words. In the short essay, they have to answer the following questions

1. Identify the appropriate form of intellectual property.

2. Describe whether a pertinent theoretical justification meets or does not meet the respective form of IP.

3. Apply the correct principle of IP protection to the given case.

4. Evaluate the lacunae in the existing IP mechanism in comparison to international framework.

5. Devise a correct way of handling the lacunas.

ESE DETAILS -

Assessment Description : Closed book exam

Assignment Details: Five problem based questions need to be answered out of seven questions.

BTGE636 - INTRODUCTION TO AVIATION (2021 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:100
Credits:2

Course Objectives/Course Description

 

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.

Course Outcome

CO1: Interpret the fundamental principles of flight based on theorems and parts of the Aircraft

CO2: Summarize the types of aircrafts and illustrate modelling of an Aircraft

CO3: Identify the types of Aero engines and Make use of Meteorology

Unit-1
Teaching Hours:10
Introduction to Principles of Flight
 

Development of Aviation- Introduction- Laws of Motion -Bernoulli’s Theorem and Venturi Effect – Aero foil- Forces on an Aircraft- Flaps and Slats- Stalling- Thrust, Basic Flight Instruments- Introduction of Radar- Requirement of Navigation

Unit-2
Teaching Hours:10
Aircrafts and Aeromodelling
 

Airfield Layout- Rules of the Air- Circuit Procedure ATC / RT Procedure Aircraft Controls- Fuselage – Main Tail Plane Ailerons- Elevators- Rudder –Landing Gear.

 Fighters- Transports- Helicopters- Foreign Aircraft History of Aero modelling- Materials used in Aero modelling - Types of Aero models

Unit-3
Teaching Hours:10
Aero Engines and Meteorology
 

Introduction of Aero engines - Types of Engines-Piston Engines -Jet Engines – Turboprop Engines, Importance of Meteorology in Aviation- Atmosphere - Clouds and Precipitation - Visibility – Humidity and Condensation

Text Books And Reference Books:

Text Books:

• Airwing Cadet Handbook, Specialized Subject SD/SW, Maxwell Press, 2016.

• Introduction to Aerospace Engineering: Basic Principles of Flight, Ethirajan Rathakrishnan, Wiley Press, 2021.

 

 

Essential Reading / Recommended Reading

Reference Books:

• An Observer’s Guide to Clouds and Weather, Toby Carlson, Paul Knight, and Celia Wyckoff,2015, American Meteorological Society.

• Aero Engines, LNVM Society, 2007, L.N.V.M. Society Group of Institutes. 

Evaluation Pattern

This Course do not have CIA 1/2/3. It has Overall CIA(out of 100 and will be Converted to 50) and ESE ( out of 100 and will be converted to 50). Total Marks=100.

BTGE637 - PROFESSIONAL PSYCHOLOGY (2021 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:100
Credits:2

Course Objectives/Course Description

 

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.

Course Outcome

CO1: Understand the frameworks for the psychology of human development.

CO2: Show greater awareness of their thinking styles, relational styles and behavioral styles of functioning

CO3: Develop interpersonal awareness and skills, especially in the context of diversity and difference

CO4: Develop preparatory skills toward effective work-life balance

CO5: Develop an overall understanding of the psychosocial skills required in professional world

Unit-1
Teaching Hours:7
Introduction to Psychological Theories
 

                                                   

 

Psychosocial development (Erickson)-Development of Cognition (Piaget)-Moral Development (Kohlberg)-Faith Development (Fowler)

Unit-2
Teaching Hours:8
Self-Awareness and Analysis
 

Thinking Styles (Cognitive distortions)- Interpersonal relationship styles (adult attachment theories)- Personality styles (Jung type indicator or Myers Briggs Type Indicator)- Coping styles: Emotion-focused and Problem-focused Analysis: Self-Analysis – Analyzing others-Body language –Facial expressions

Unit-3
Teaching Hours:7
Social Influences
 

                                                                                 

Conformity: Asch’s Research on Conformity-Factors Affecting Conformity; Compliance -The Underlying Principles - Ingratiation;Obedience to Authority-Destructive Obedience

Unit-4
Teaching Hours:8
Approaches to work motivation and job design
 

                              Overview of motivation - Need theories - Expectancy theory – Justice and citizenship theories - Goal-setting theory - Goals and self -regulation - Self-concept and individual differences in motivation - Pay and motivation - Motivation through job redesign                                                        

 

 

Text Books And Reference Books:

Baron, R. A., (2012), Psychology,  5th edition. Pearson Education India

Baron, R. A., & Branscombe, N. R. (2006). Social psychology. Pearson Education India.

Nelson Goud and Abe Arkoff (2005), Psychology and Personal Growth, Edition, Allyn and Bacon.

Essential Reading / Recommended Reading

 Nelson Jones. (2006), Human Relationship skills: Coaching and self-coaching, 4th edition, Routledge. 

Evaluation Pattern

CIA-1

CIA-2(MSE)

CIA-1

ESE

TOTAL

20

50

20

50

100

1.     CIA =50 marks:   CIA1/2/3 Marks would be converted to 45 and 5 marks for attendance

2.     ESE would be for 50 marks

 

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

 

Course Description
Data Analysis using SPSS is specially designed to provide the requisite knowledge and skills in Data Analytics. The course covers concepts of Basics about Statistics, Data handling, Data Visualization, Statistical analysis, etc. This course will build a base for advance data analysis skills.

Course objectives

After the completion of the course, you should be able to:


a. Understand basic concepts of statistics and computer software SPSS
b. Select appropriate Statistical test for particular type of data
c. Recognize and interpret the output from statistical analysis

Course Outcome

CO1: Students will understand the concepts involved for analyzing Business data

CO2: Students will be able to understand how to use software like SPSS to analyse data

CO3: Students will be able to appreciate the use of Data Analytics for business decision making

Unit-1
Teaching Hours:2
Introduction to data Analysis
 

Introduction to Statistics and SPSS package viz.,, Types of data, data editing, coding, cleaning, outliers, missing data, import, export, data labeling, transforming data.

Unit-2
Teaching Hours:2
Data Visualization
 

Graphs, scatter plot, charts, frequency tables, histogram, Boxplot, pie chart, etc

Unit-3
Teaching Hours:4
Descriptive Statistics and Hypothesis testing
 

Basic statistics like mean, median, mode, SD, Examine relationship between variables example correlation, regression, etc., Compare groups to determine if there are significant differences between these groups example T-test, ANOVA etc., and to measure the association/independence using Chi-square., etc.

Unit-4
Teaching Hours:4
Logistic Regression
 

Application of logistic regression in SPSS using case study

Unit-5
Teaching Hours:4
Factor analysis
 

Application of factor analysis in SPSS using case study

Unit-6
Teaching Hours:14
Cluster Analysis and Discriminant analysis
 

 

Application of Cluster analysis and Discriminant in SPSS using case study