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

  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:

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:

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

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

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

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

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

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

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

ESE:30/100

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.

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.

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

ESE-30/100

●      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

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.

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

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

ESE 30 marks

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.

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

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

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.

ESE 30 marks

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

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

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

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

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

Maximum Marks : 50

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

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.  

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

·

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

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.

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

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, ” 10^th  Edition. Pearson Education, 2007

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

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)

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.

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

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

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

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)

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

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. 

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.

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.

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.

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

Components of the CIA

CIA I  :  Subject Assignments / Online Tests                  : 10 marks

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

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

Attendance                                                                           : 05 marks

            Total                                                                                       : 50 marks

Mid Semester Examination (MSE) : Theory Papers:

• 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

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. 

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.

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. 

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.

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 

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.

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.

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

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.

ESE 30 Marks

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.

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

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

ESE - 30 Marks

 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.

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

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

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

End Semester Exam - 50 Marks

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

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

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.

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.

ESE - 30% out of 100

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

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.

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

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.

ESE: 50

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.

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.

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.

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.

ESE-50

• 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.

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.

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)

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.

ESE=50

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

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.   

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]

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.

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

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

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

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

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

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. 

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.

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.

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.

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

Components of the CIA

CIA I  :  Subject Assignments / Online Tests                  : 10 marks

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

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

Attendance                                                                           : 05 marks

            Total                                                                                       : 50 marks

Mid Semester Examination (MSE) : Theory Papers:

• 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

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

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

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.

End Semester Examination 30%

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.

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.

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

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

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

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.

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.

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.

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.

Weightage for ESE: 50

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.

 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.

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)

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” 8^th 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)

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)

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.

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.

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

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

ESE 50 Marks

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

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.

Passing marks 40% min

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

● 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

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.

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

ESE:30

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

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

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

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

ESE 30%

·        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.

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

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

ESE - 30 Marks

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.

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

ESE 50 marks

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.

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.

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

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

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. 

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

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

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

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

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

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

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

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.

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

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

CIA II -midsem 50 marks

CIA III - 20 marks

ESE - 100 marks

·         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.

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

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.

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

CIA II - midsem 50 marks

CIA III - 20 marks

ESE - 100 marks

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.

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.

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

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.

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

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.

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.

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.

ESE - 50% out of 100

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.

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 

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