CHRIST (Deemed to University), Bangalore

DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING

School of Business and Management

Syllabus for
Bachelor of Technology in Electronics and Computer Engineering(with specialization in Artificial Intelligence and Machine Learning)
Academic Year  (2023)

 
3 Semester - 2022 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
CY321 CYBER SECURITY Skill Enhancement Courses 2 0 0
EC333P ELECTRONIC DEVICES AND CIRCUITS Core Courses 5 4 100
ECHO341CSP INTRODUCTION TO CRYPTOLOGY Minors and Honours 4 4 50
ELC331 MATHEMATICS FOR INTELLIGENT SYSTEMS Core Courses 3 3 100
ELC332P DATA STRUCTURES AND ALGORITHMS Core Courses 5 4 100
ELC334 DIGITAL ELECTRONICS Core Courses 5 4 100
ELC335 PROGRAMMING LANGUAGE PARADIGM Core Courses 3 3 100
HS325 PROFESSIONAL ETHICS Core Courses 2 2 50
4 Semester - 2022 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
BS451 ENGINEERING BIOLOGY LABORATORY Core Courses 2 2 50
EC434 COMPUTER ORGANIZATION AND PROCESSORS Core Courses 3 3 100
EC435 COMPUTER NETWORKS Core Courses 3 3 100
ECHO441CS INTRODUCTION TO BLOCKCHAIN Minors and Honours 12 4 100
ELC431P OBJECT ORIENTED PROGRAMMING Core Courses 5 4 100
ELC432 ARTIFICIAL INTELLIGENCE Core Courses 3 3 100
ELC433 SIGNALS AND SYSTEMS Core Courses 3 3 100
EVS421 ENVIRONMENTAL SCIENCE Skill Enhancement Courses 2 0 0
5 Semester - 2021 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
CSOE561E04 PYTHON FOR ENGINEERS Interdisciplinary Elective Courses 3 3 100
CSOE561E05 BASICS OF MACHINE LEARNING Interdisciplinary Elective Courses 3 3 100
EC532P DIGITAL SIGNAL PROCESSING Core Courses 5 4 100
EC533P MICROCONTROLLER BASED SYSTEM DESIGN Core Courses 5 4 100
ECHO541CSP INTRODUCTION TO CRYPTOLOGY Minors and Honours 4 4 50
ECHO542CS INTRODUCTION TO BLOCKCHAIN Minors and Honours 4 4 100
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
ELC531P DATABASE MANAGEMENT SYSTEMS Core Courses 5 4 100
ELC541E04 OPERATING SYSTEMS Discipline Specific Elective Courses 3 3 50
IC521 CONSTITUTION OF INDIA Skill Enhancement Courses 2 0 50
NCCOE1 NCC1 Interdisciplinary Elective Courses 3 3 100
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
EC631P VLSI DESIGN Core Courses 5 4 100
EC635 SERVICE LEARNING Core Courses 2 2 100
EC637 COMPUTER NETWORKS - 3 3 100
ECHO641CSP COMPUTING SYSTEM SECURITY Minors and Honours 75 3 100
ECHO642CS CRYTOGRAPHY AND SECURITY IMPLEMENTATION Minors and Honours 3 3 100
ELC632P INTRODUCTION TO MACHINE LEARNING USING PYTHON Core Courses 5 4 100
ELC644E07 BIG DATA ANALYTICS Electives 3 3 100
ELC645E02 AUTOMOTIVE ELECTRONICS Electives 3 3 100
ELC645E03 RTOS Electives 3 3 100
HS621 PROJECT MANAGEMENT AND FINANCE Core 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
ELC731P INTERNET OF THINGS Core Courses 5 4 100
ELC732 DIGITAL IMAGE PROCESSING Core Courses 3 3 100
ELC733 PYTHON FOR MACHINE LEARNING Core Courses 3 3 100
ELC744E01 MOBILE APPLICATION DEVELOPMENT Discipline Specific Elective Courses 3 3 100
ELC781 INTERNSHIP Project 2 2 50
ELC782 PROJECT WORK PHASE I Project 12 6 100
ME761E03 BASIC AUTOMOBILE ENGINEERING Interdisciplinary Elective Courses 3 3 100
ME761E04 SMART MATRIALS AND APPLICATIONS Interdisciplinary Elective Courses 3 3 100
PH736OE1 NANO MATERIALS AND NANOTECHNOLOGY Interdisciplinary Elective Courses 3 3 100
8 Semester - 2020 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
ELC841E05 HIGH SPEED NETWORKS Electives 3 3 100
ELC881 PROJECT WORK PHASE II Project 12 6 100

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

EC333P - ELECTRONIC DEVICES AND CIRCUITS (2022 Batch)

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

Course Objectives/Course Description

 

The aim of this course is to familiarize the student with the principle of operation, capabilities and limitation of various electron devices so that he or she will be able to use these devices effectively.

Course Outcome

CO1: Understand the biasing and small signal analysis of BJT. [L2]

CO2: Understand the biasing and small signal analysis of FET. [L2]

CO3: Construct the low frequency and high frequency BJT amplifiers. [L3]

CO4: Examine the feedback amplifiers for different applications [L4]

CO5: Perform analysis of the cascading stages of amplifiers and working principle of power devices. [L4]

Unit-1
Teaching Hours:9
BJT ? BIASING AND SMALL SIGNAL ANALYSIS
 

1. DC Biasing - BJTs : Operating Point, Transistor Biasing circuits (Fixed Bias, Emitter Bias, Voltage Divider Bias, DC Bias with voltage feedback. Transistor as a switch.

2. BJT AC Analysis: BJT as amplifier. Small signal equivalent circuits (Low frequency re and h models only). Small signal analysis of CE, CB, CC (Voltage Divider Bias) configurations using re and hybrid  model – with and without bypass capacitor.

Unit-2
Teaching Hours:9
FET ? BIASING AND AMPLIFIERS
 

1. JFET: Construction, Operation, Characteristic, Shockley's Equation, Transfer Characteristics and Applications, MOSFET :Enhancement type MOSFET and Depletion MOSFET – Construction, Operation and Characteristics, Handling precautions for MOSFET 

2. FET Biasing: Fixed Bias Configuration, Self – Bias Configuration, Voltage Divider Biasing. Depletion Type MOSFETs, Enhancement Type MOSFETs, FET Amplifiers: FET Small Signal Model  

Unit-3
Teaching Hours:9
FREQUENCY RESPONSE AND HIGH FREQUENCY ANALYSIS
 

1. General shape of frequency response of amplifiers. Definition of bel, decibel, cut off frequencies and bandwidth. Low frequency analysis of amplifiers to obtain lower cut off frequency.

2. Hybrid – pi equivalent circuit of BJTs. High frequency analysis of BJT amplifiers to obtain upper cut off frequency

Unit-4
Teaching Hours:9
FEEDBACK AMPLIFIERS
 

Feedback Amplifiers: Negative and positive feedback. Properties of negative  and positive feedback, negative feedback configurations, analysis of negative feedback amplifiers for gain, frequency response, input impedance, and output impedance of different configurations (voltage series, current series, voltage shunt, and current shunt)

Unit-5
Teaching Hours:9
CASCADE SYSTEMS AND POWER CONTROL DEVICES
 

CASCADE SYSTEMS: Analysis of frequency response and gain for BJT and FET amplifiers

POWER CONTROL DEVICES: Power control devices: PNPN diode (Shockley diode)  SCR characteristics – LASCR (Light Activated SCR) – TRIAC – DIAC – Structure & Characteristics. Characteristics and equivalent circuit of UJT - intrinsic stand-off ratio

Text Books And Reference Books:

T1. Robert L. Boylestead & Louis Nashelsky, “Electronic Devices and Circuit Theory”, 10th ed., Pearson Education, 2009.

T2. Jacob Millman & Christos C. Halkias, “Electronic Devices and Circuits”, Tata McGraw-Hill Education Pvt. Ltd., 2010.

Essential Reading / Recommended Reading

R1. Millman J. and Halkias C. " Integrated Electronics ", Tata McGraw-Hill Publishing, 2000

R2. Donald A Neamen, “Electronic Circuit Analysis and Design”, 3/e, TMH.

R3. Albert Paul Malvino, Electronic Principles, 8th Ed, McGraw-Hill Education, 2016.

R4. Sedra and Smith.” Microelectronic Circuits”, 6/e, Oxford University Press, 2010.

R5. David A. Bell, “Electronic Devices and Circuits”, 4th Edition, Prentice Hall of India, 2007.  

Evaluation Pattern

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.

ECHO341CSP - INTRODUCTION TO CRYPTOLOGY (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:50
Credits:4

Course Objectives/Course Description

 

Identify, formulate, research literature, and analyse complex engineering

problems reaching substantiated conclusions using first principles of mathematics, natural

sciences, and engineering sciences.

Course Outcome

CO-1: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialisation for the solution of complex engineering problems.

Unit-1
Teaching Hours:9
Basic Concepts of Number Theory and Finite Fields:
 

Divisibility and the divisibility algorithm, Euclidean algorithm, Modular arithmetic, Groups, Rings and Fields, Finite fields of the form GF(p), Polynomial arithmetic, Finite fields of the form GF(2n), Galois group of a field extensions, Fixed field and Galois extensions, Fundamental theorem of Galois Theory

Unit-2
Teaching Hours:9
Classical Encryption Techniques
 

Symmetric cipher model, Substitution techniques, Transposition techniques, Steganography, Traditional Block Cipher structure, Data Encryption Standard (DES) 

Unit-3
Teaching Hours:9
Pseudo-Random-Sequence Generators
 

The AES Cipher, Linear Congruential Generators, Linear Feedback Shift Registers, Design and analysis of stream ciphers, Stream ciphers using LFSRs 

Unit-4
Teaching Hours:9
Principles of Public-Key Cryptosystems
 

Prime Numbers, Fermat‘s and Euler‘s theorem, Primality testing, Chinese Remainder theorem, discrete logarithm, The RSA algorithm, Diffie - Hellman Key Exchange, Elliptic Curve Arithmetic, Elliptic Curve Cryptography

Unit-5
Teaching Hours:9
One-Way Hash Functions
 

Background, Snefru, N-Hash, MD4, MD5, Secure Hash Algorithm [SHA],One way hash functions using symmetric block algorithms, Using public key algorithms, Choosing a one-way hash functions, Message Authentication Codes. Digital Signature Algorithm, Discrete Logarithm Signature Scheme

Text Books And Reference Books:

 

  1. Behrouz A. Forouzan and D. Mukhopadhyay, Cryptography & Network Security, McGraw Hill, New Delhi.
  2. William Stallings, Cryptography and Network Security: Principles and Practice, Prentice-Hall
Essential Reading / Recommended Reading

Cryptography and Network Security, Atul Kahate, TMH, 2003.

Evaluation Pattern

CIA- 50

ESE-50

ELC331 - MATHEMATICS FOR INTELLIGENT SYSTEMS (2022 Batch)

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

Course Objectives/Course Description

 

The course will lay down the basic concepts and techniques of linear algebra, differential equation, Analytical optimization and graph theory as applied to intelligent system design.

Course Outcome

CO1: Apply the understanding of working with data in matrix form for solving systems of linear algebraic equations, for finding the basic matrix decompositions with the general understanding of their applicability in intelligent systems.

CO2: Understand the notion of an abstract vector space and how coordinates, and matrices of linear transformations, arise from the underlying linearity structures imposed on the system

CO3: Apply multivariable and vector-valued functions and their derivatives, using gradient algorithms to determine local/global maxima and minima, saddle points.

CO4: Analyze the type of optimization problem and apply suitable algorithm to find the optimum value of the objective function

CO5: Understand the fundamental concepts in graph theory and Apply algorithms and theorems from graph theory on solving problems

Unit-1
Teaching Hours:9
Linear Algebra
 

Introduction, Gaussian Elimination ( for solutions and Inverse, Nonsingular versus Singular) ,Determinants and Properties of the Determinant.

Vector Spaces (column, Row Null and left nullspace), Linear Independence, Basis and Dimension, Linear Transformations, Eigenvalues and Eigenvectors, Diagonalization of a Matrix, Positive Semi definite and Positive Definite.

Unit-2
Teaching Hours:9
Multivariant Calculus
 

Partial derivatives,Taylors Series and Linearization, Gradient, directional derivative. Vector and matrix calculus, Calculus: Convexity and concavity of functions of one and two variables, local/global maxima and minima, saddle point

Unit-3
Teaching Hours:9
Statistics and Probability
 

Principles of Probablity Theory( Expectation, Variance, density , Bayes theorem, Central limit Theory), Standard Distributions (Binomial, Poisson, Normal, Chi-squared,t-distribution) , Maximum Likelyhood Theory, Statistical Tests(type I, Type II error, T-test, Chi-squared Test), Confidence Intervals

Unit-4
Teaching Hours:9
Optimization
 


Objective function, Constraints; Formulation of simple design problems as mathematical programming problems. Classification of optimization problems, Optimization with linear constraint using  Lagrangian function, Standard form of linear programming (LP) problem- Graphical method, Steepest descent method, Newtons Method, Convex optimization.

Unit-5
Teaching Hours:9
Graph Theory
 

Graph Theory: Graph Terminology and Special Types of Graphs, Planar Graphs, Graph Coloring, Trees, Graph Minor. Vertex cover, matching, path cover, connectivity, edge coloring, vertex coloring, list coloring; Planarity, Perfect graphs; other special classes of Graphs Connectivity, Hamilton Paths-Travelling salesman problem . Shortest path algorithm-Dijkstra’s algorithm

Text Books And Reference Books:

T1.  Gilbert Strang, Linear Algebra and its applications, 4th Ed, Cengage Learning, 2006

T2.  MP Deisenroth, A A Faisal, C S Ong, Mathematics for Machine learning, Cambridge University, 2020

T3.  Phil Dyke, Advanced Calculus, Macmillan International Higher Education, 1998

T4.  Fletcher R., Practical Methods of Optimization, John Wiley, 2000

T5.  Reinhard Diestel, "Graph Theory", Springer (2010)

Essential Reading / Recommended Reading

R1.  Singiresu S Rao, Engineering Optimization, 4th ed, Wiley, 2009

R2.  Jorge Nocedal and Stephen J. Wright: "Numerical Optimization", second ed,1999

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.

ELC332P - 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

 

This course is designed to make the students familiar with basic techniques of algorithm analysis, to understand concepts of searching and sorting techniques and to assess how the choice of data structures impacts the performance of a program. 

Course Outcome

CO1: Explain linear and non-linear data structures like stack, queue, linked list, tree and graph

CO2: Explain data structures operations including insertion, deletion, traversal, searching, and sorting

CO3: Understand the concept and operations of singly linked list, circular linked list and double linked list

CO4: Understand the functions of data warehousing including the components, architecture mapping, data extraction and data cleanup

CO5: Demonstrate online analytical processing (OLAP) as per the OLAP guidelines using OLAP tools

CO6: Implement programs to summarize the operations of data structures

Unit-1
Teaching Hours:9
INTRODUCTION
 

Definition and basics of: Data Structure, ADT, Algorithms, Time and Space Complexity, Asymptotic Notations (O, θ, Ω), Time complexity computation of non-recursive algorithms (like Matrix addition, Selection sort – using step count), Array – basic operations, concept of multi-dimensional array, Polynomial operations using Array, Sparse Matrix

Unit-2
Teaching Hours:9
STACK AND QUEUE
 

Stack ADT: basic operations, Queue ADT: basic operations, Circular Queue, Evaluation of Expressions, Another application or Mazing Problem

Unit-3
Teaching Hours:9
LINKED LIST
 

Singly Linked List: concept, representation and operations, Circular Linked List, Polynomial and Sparse Matrix operations using LL, Doubly Linked List: basic concept

Unit-4
Teaching Hours:9
INTRODUCTION TO ALGORITHMS
 

Introduction, Notion of Algorithm, Fundamentals of Algorithmic Solving, Fundamentals of the Analysis Framework, Asymptotic Notations and Basic Efficiency Classes, Mathematical Analysis of Non-recursive Algorithm, Mathematical Analysis of Recursive Algorithm and examples, Empirical Analysis of Algorithms and Algorithm Visualization

Unit-5
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, DFS and BFS. Decrease and Conquer: Insertion Sort and Topological Sorting and Binary Search, Warshall’s and Floyd’s Algorithm. Greedy Techniques: Prim’s Algorithm, Kruskal’s Algorithm, Dijkstra’s Algorithm and Huffman trees

Text Books And Reference Books:

T1. Sahni Horwitz,, Freed Anderson, Fundamentals of Data Structures in C, 2nd Edition (or latest) , University Press.\

T2. Anany Levitin, “Introduction to the Design and Analysis of Algorithm”, 3/e, Pearson Education Asia, 2008, (Reprint 2012).

T3. Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser, “Data Structures and Algorithms in Java”, 6/e, Wiley, 2014.

Essential Reading / Recommended Reading

R1. TharejaReema, Data Structures Using C, 2nd Edition, Oxford University Press

R2Tanenbaum, Langsam, Augenstein, Data Structures using C, Pearson

R3. T. H Cormen, C E Leiserson, R L Rivest and C Stein: “Introduction to Algorithms”, 3rd Edition, The MIT Press, 2014.

R4.Ellis Horowitz, Sartaj Sahni and Sanguthevar Rajasekaran, Computer Algorithms, Second Edition, Universities Press, 2007.

Evaluation 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 to pass

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

                           

·        

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

          Minimum marks required to pass in practical component is 40%.

·         Pass in practical component is eligibility criteria to attend Theory End semester examination for the same course.

·         A minimum of 40 % required to pass in ESE -Theory component of a course.

·         Overall 40 % aggregate marks in Theory & practical component, is required to pass a course.

·         There is no minimum pass marks for the Theory - CIA component.

·         Less than 40% in practical component is refereed as FAIL.

·         Less than 40% in Theory ESE is declared as fail in the theory component.

·         Students who failed in theory ESE have to attend only theory ESE to pass in the course

ELC334 - DIGITAL ELECTRONICS (2022 Batch)

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

Course Objectives/Course Description

 

The aim of this course is to study the basics of digital circuits and learn methods and fundamental concepts used in the design of digital systems.

Course Outcome

CO1: To apply the principles of Boolean algebra and K-map to design combinational circuits

CO2: To analyze the operation of sequential circuits built with various flip-flops and design of counters, registers

CO3: To use state machine diagrams to design finite state machines using various types of flip-flops and combinational circuits with prescribed functionality.

CO4: To understand the concepts of data paths, control units, and micro-operations and building blocks of digital systems

CO5: To design combinational and sequential circuits using Verilog HDL modeling.

Unit-1
Teaching Hours:9
COMBINATIONAL CIRCUITS
 

Design procedure – Four variable Karnaugh Maps, Adders-Subtractors – Serial adder/Subtractor - Parallel adder/ Subtractor- Carry look ahead adder- BCD adder, Magnitude Comparator. Multiplexer/ Demultiplexer,Encoder / decoder, parity checker, Code converters. Implementation of combinational logic using MUX, ROM, PAL and PLA

Unit-2
Teaching Hours:9
SEQUENTIAL CIRCUITS
 

Classification of sequential circuits, Moore and Mealy -Design of Synchronous counters: state diagram- State table –State minimization –State assignment- ASM-Excitation table and maps-Circuit implementation - Universal shift register – Shift counters – Ring counters

Unit-3
Teaching Hours:9
ASYNCHRONOUS SEQUENTIAL CIRCUITS
 

Design of fundamental mode and pulse mode circuits – primitive state / flow table – Minimization of primitive state table –state assignment – Excitation table – Excitation map- cycles – Races, Hazards: Static –Dynamic –Essential –Hazards elimination.

Unit-4
Teaching Hours:9
DIGITAL INTEGRATED CIRCUITS
 

Introduction – Special Characteristics – Bipolar Transistor Characteristics – RTL and DTL circuits – Transistor-Transistor Logic (TTL) Emitter Coupled Logic (ECL) – Metal Oxide Semiconductor (MOS) – Complementary MOS (CMOS) – CMOS Transmission Gate circuits

Unit-5
Teaching Hours:9
VERILOG HDL
 

Basic Concepts: VLSI Design flow, identifiers, gate primitives, value set, ports, gate delays, structural gate level modeling, Behavioral modeling, Data flow modeling, Design hierarchies, Structural gate level description of combinational and sequential circuits.

Text Books And Reference Books:

 

T1. M. Morris Mano, Michael D. Ciletti, “Digital Design” 5thEdition, Prentice Hall of India Pvt. Ltd., New Delhi, 2015/Pearson Education (Singapore) Pvt. Ltd., New Delhi, 2003.

 

T2. Samir Palnitkar, “Verilog HDL”, 2 edition, Pearson Education, 2003

T3. Peter.J.Ashenden, “Digital Design: An Embedded Systems Approach Using Verilog”, Elsevier 2010

Essential Reading / Recommended Reading

 

R1. John .M Yarbrough,” Digital Logic Applications and Design, Thomson- Vikas Publishing house, New Delhi, 2006.

 

R2. S. Salivahanan and S. Arivazhagan, “Digital Circuits and Design, 5th ed., Vikas Publishing House Pvt. Ltd, New Delhi, 2016.

 

R3. Charles H.Roth, ” Fundamentals of Logic Design”, Thomson Publication Company, 2012.

R4. Donald P.Leach and Albert Paul Malvino, “Digital Principles and Applications”,6th Edition, Tata McGraw Hill Publishing Company Limited, New Delhi, 2012.

Evaluation Pattern

Theory CIA - 30 marks

CIA will be conducted for 50 marks. Later the marks will be scaled down to 30 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

Theory ESE - 30 marks

End Semester Examination (ESE):
The ESE is conducted for 100 marks of 3 hours duration. (100 marks will be scaled down to 30 marks)

 

Practical - 35 marks

Practical assessment depends on the student's lab discipline, regular attendance, conduction of the lab, observation and record submission and final lab exam.

Attendance - 5 marks

In total, the course is evaluated for 100 (30+30+35+5) marks.

ELC335 - PROGRAMMING LANGUAGE PARADIGM (2022 Batch)

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

Course Objectives/Course Description

 

This course aims to explore modern programming languages and the techniques used for programming  in order to get idea on evaluation of programming languages and also helps students to analyze a given program from good programming practice perspective

Course Outcome

CO1: Write programs related to syntax and semantics

CO2: Compare programs between C, Ada, Perl and Small Talk

CO3: Write programs using scripting languages

CO4: Demonstrate event-driven and concurrent programming using prolog

CO5: Apply prolog for developing distributed systems

Unit-1
Teaching Hours:9
INTRODUCTION
 

The art of Language design – Programming language spectrum - Compilation and Interpretation – Evaluation of Programming languages – Syntax and Semantics of Language C-lite - Names – Types – Type Systems - Binding – Scope – Static – Dynamic – Abstract Data types

Unit-2
Teaching Hours:9
SEMANTICS
 

Expression – Assignment - Control Flow – Input/Output – Exception Handling – State Transformation – Partial Functions – Semantics with Dynamic Typing – Formal Treatment of Semantics

Unit-3
Teaching Hours:9
FUNCTIONS
 

Call and Return – Parameter Passing – Function Declaration – Semantics Of Call and Return – Formal Treatment of Types and Semantics – Memory Management – Dynamic Arrays – Garbage Collection.

Unit-4
Teaching Hours:9
PROGRAMMING TECHNIQUES
 

Imperative programming – C – ADA – Perl – Object Oriented Programming – Small TalkJava– Python – Functional Programming – Scheme – Haskell

Unit-5
Teaching Hours:9
MODERN PROGRAMMING TECHNIQUES
 

Logic Programming – Prolog – Event-Driven programming – Concurrent Programming – Concepts – Synchronization Strategies – Language Level Mechanism - Interprocess COMMUNICATION – Scripting LANGUAGES

Text Books And Reference Books:

T1. Allen B. Tucker and Robert E. Noonan, ―Programming Languages – Principles and Paradigms, Second Edition, Tata McGraw Hill, 2009

Essential Reading / Recommended Reading

R1. Robert W. Sebesta, ―Concepts of Programming Languages, Sixth Edition, Addison Wesley, 2003

R2. Michael L Scott, ―Programming Language Pragmatics, Third Edition, Morgan Kauffman, 2009

Evaluation Pattern

As per University Norms

HS325 - 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

 

(a) To understand the moral values that ought to guide the Engineering profession.

(b) To resolve the moral issues in the profession.

 

Course Outcome

CO1: Outline professional ethics and human values by realizing the holistic attributes.{L1}{PO6,PO8}

CO2: Specify the Engineering Professional Ethics to identify problems related to society, safety, health & legal aspects. {L1}{PO6,PO8}

CO3: Explain the importance of being ethical while using technology in the digital space. {L2}{PO8,PO12}

CO4: Understand the ethical principles and behaviors laid down by IEEE. {L2}{PO6,PO8,PO9,PO12}

CO5: Explain the Importance of ethical conduct to safeguard environment and its resources with respect to electronics engineering. {L1}{PO7,PO8}

Unit-1
Teaching Hours:6
INTRODUCTION TO ETHICS
 

Introduction to Profession, Engineering and Professionalism, Three types of Ethics / Morality , Positive and Negative faces of Engineering Ethics

Unit-2
Teaching Hours:6
RESPONSIBILITY IN ENGINEERING AND ENGINEERING ETHICS
 

Introduction, Engineering Standards, Blame – Responsibility and Causation, Liability, Design Standards.

Senses of 'Engineering Ethics' - variety of moral issued - types of inquiry - moral dilemmas - moral autonomy - Kohlberg's theory - Gilligan's theory - consensus and controversy – Models of Professional Roles - theories about right action - Self-interest - customs and religion - uses of ethical theories.

 

Unit-3
Teaching Hours:6
SOCIAL AND VALUE DIMENSIONS IN TECHNOLOGY
 

Technology – The Promise and Perils, Computer Technology – Privacy and Social Policy, Ownership of Computer Software and public Policy, Engineering Responsibility in Democratic Deliberation on Technology Policy, The Social Embeddedness of Technology.

Unit-4
Teaching Hours:6
ELECTRONICS ENGINEERING ETHICS
 

Ethics in Electronics Engineering - IEEE Code of Ethics, Computer Ethics, Case Studies on ethical conflicts, Corporate Social Responsibility

Ethics in Electronics Business – HR, Marketing, Finance and Accounting, Production and Operation, Tendering and contracts, Ethical behaviour expected out of a electronic contractor

 

Unit-5
Teaching Hours:6
ETHICS AND ENVIRONMENT
 

Environment in Law and Court Decisions, Criteria for “Clean Environment”, E-Waste Management, ethical responsibility towards e-waste management, radiation effects on the society, ethical behaviour of the stakeholders running the communication business 

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. Charles D. Fleddermann, “Engineering Ethics”, Pearson Education / Prentice Hall, New Jersey, 2004 (Indian Reprint).

R2. Charles E Harris, Michael S. Protchard and Michael J Rabins, “Engineering Ethics – Concepts and Cases”, Wadsworth Thompson Learning, United States, 2000 (Indian Reprint now available)

R3. John R Boatright, “Ethics and the Conduct of Business”, Pearson Education, New Delhi, 2003

R4. Edmund G Seebauer and Robert L Barry, “Fundamentals of Ethics for Scientists and Engineers”, Oxford University Press, Oxford, 2001.

 

Evaluation Pattern

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 50 marks of 2 hours duration.
The syllabus for the theory papers are divided into FIVE units and each unit carries equal weightage in terms of marks distribution.

 

BS451 - ENGINEERING BIOLOGY LABORATORY (2022 Batch)

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

Course Objectives/Course Description

 

Understanding and application of MATLAB and TINKERCAD for biological analysis which would results in better healthcare and any engineer, irrespective of the parent discipline (mechanical, electrical, civil, computer, electronics, etc.,) can use the disciplinary skills toward designing/improving biological systems. This course is designed to convey the essentials of human physiology.The course will introduce to the students the various fundamental concepts in MATLAB and TINKERCAD for numerical analysis and circuit design using arduino.

 

Course Outcome

CO1: Examine the various applications of bioengineering and using common tool boxes for analysing medical information.

Unit-1
Teaching Hours:30
LIST OF EXPERIMENTS
 

1.     Blood Pressure Measurement using Arduino

2.     Measuring HRV using the data from pulse measurement in Matlab.

3.     Measure heart rate and SPO2 with Arduino

4.     Measuring BMI, heart rate, SPO2, HRV using MATLAB and indicating health of person.

5.     Analyzing breast cancer, EEG, ECG and CT images using MATLAB from online data sources and detecting irregularties (arrhythmia, tumor, cancer, epilepsy).

6.     Analyzing force developed in muscles when performing any given task (to move servo motor and subsequently robotic arm).

7.     Measuring water content in given soil using temperature, pH using Arduino.

8.     IR thermal imaging to determine effect of mobile radiation.

9.     Synthesis of biopolymers from starch.

 

Text Books And Reference Books:

NIL

 

 

Essential Reading / Recommended Reading

 NIL

 

 

 

 

Evaluation Pattern

As per university norms

EC434 - COMPUTER ORGANIZATION AND PROCESSORS (2022 Batch)

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

Course Objectives/Course Description

 

To discuss the basic structure of a digital computer and to study in detail the organization of the Control unit, the Arithmetic and Logical unit, Memory unit and Intel Processors.

Course Outcome

CO1: Summarize the architectural features of a computer

CO2: Discover the basic functional units in ALU and perform various arithmetic operations of ALU

CO3: Demonstrate the dataflow and program execution process in Computer

CO4: Summarize various memory architectures and their data storage behaviour

CO5: Interpret unique architectural features of 8086 and Pentium processors.

Unit-1
Teaching Hours:9
BASIC STRUCTURE OF COMPUTERS
 

A Brief History of computers, Von Neumann Architecture, Harvard architecture, Computer Components, Functional units - Basic operational concepts - Bus structures - Software performance – Memory locations and addresses-Addition and subtraction of signed numbers – Design of fast adders – Multiplication of positive numbers - Hardware Implementation- Signed operand multiplication.

Unit-2
Teaching Hours:9
ARITHMETIC & LOGIC UNIT
 

Booths Algorithm- fast multiplication – Integer division & it’s Hardware Implementation – Restoring and Non Restoring algorithms-Fundamental concepts – Execution of a complete instruction – Multiple bus organization – Hardwired control – Micro-programmed control - Pipelining – Basic concepts – Data hazards – operand forwarding-Instruction hazards- Instruction Set architecture for logical operation

Unit-3
Teaching Hours:9
8086 MICROPROCESSOR
 

Intel 8086 Microprocessor - Internal architecture – segment registers- 8086 memory organization–Flag Register-logical and physical address calculation-Block diagram of Minimum and maximum mode  and its operations – Interrupt and Interrupt applications-Assembly language programming of 8086.

Unit-4
Teaching Hours:9
INTERFACING WITH 8086
 

Memory Interfacing and I/O interfacing - Parallel communication interface – Serial communication interface – Timer –Interrupt controller – DMA controller – Programming and applications

Unit-5
Teaching Hours:9
PENTIUM MICROPROCESSOR
 

Advanced Intel Microprocessors- Reduced Instruction cycle – five stage instruction pipe line – Integrated coprocessor – On board cache – Burst Bus mode. Pentium – super scalar architecture – u-v pipe line – branch prediction logic – cache structure – BIST (built in self-test) – Introduction to MMX technology. Case Study

Text Books And Reference Books:

T1. Carl Hamacher, Zvonko Vranesic and Safwat Zaky, 7th Edition “Computer Organization”, McGraw-Hill, 2011

T2. Douglous V. Hall “Microprocessor and Interfacing”  3rd edition ,Tata McGraw Hill,2015.

T3.James L. Antonakos , “ The Pentium Microprocessor ‘’ Pearson Education, 2007

Essential Reading / Recommended Reading

R1. William Stallings, “Computer Organization and Architecture – Designing for Performance”, 10h Edition, Pearson Education, 2015.

R2. David A.Patterson and John L.Hennessy, “Computer Organization and Design: The hardware / software interface”, 3rd Edition, Morgan Kaufmann, 2008

R3. John P.Hayes, “Computer Architecture and Organization”, 4th  Edition, McGrawHill, 2003.

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

 

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.

EC435 - COMPUTER NETWORKS (2022 Batch)

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

Course Objectives/Course Description

 

This course aims to introduce the concepts, terminologies, and technologies used in modern data communication and computer networking. It also gives an introduction to the IEEE standards used for WLAN for physical ant MAC layer.

Course Outcome

CO1: Explain the network models and terminologies including topologies, transmission media and line coding for a data communication system.

CO2: Understand the data link layer services for error control using parity check, Hamming & cyclic codes and flow control techniques using stop & wait, stop & wait ARQ, Go-back n ARQ protocols.

CO3: Find the path for network layer packet delivery for a given topology using intradomain routing protocols

CO4: Understand the essential principles of transport layer including reliable data transfer, congestion control and quality of service

CO5: Describe the MAC layer functions including DCF,PCF access schemes of Wireless LAN from IEEE 802.11 draft standard

Unit-1
Teaching Hours:9
DATA COMMUNICATIONS
 

Components – Direction of Data flow – networks – Components and Categories – types of Connections – Topologies –Protocols and Standards – ISO / OSI model – Transmission Media – Coaxial Cable – Fiber Optics – Line Coding – Modems – RS232 Interfacing sequences. TCP/IP.

Unit-2
Teaching Hours:9
DATA LINK LAYER
 

Error – detection and correction – Parity – LRC – CRC – Hamming code – Flow Control and Error control: stop and wait – go back N ARQ – selective repeat ARQ- sliding window techniques – HDLC. LAN: Ethernet IEEE 802.3, IEEE 802.4, and IEEE 802.11

Unit-3
Teaching Hours:9
NETWORK LAYER
 

Internetworks - Packet Switching and Datagram approach – IP addressing methods IP Multicasting and broadcasting– Subnetting – Routing – Distance Vector Routing – Link State Routing – Routers.

Unit-4
Teaching Hours:9
TRANSPORT LAYER
 

Duties of transport layer – Multiplexing – Demultiplexing – Sockets – User Datagram Protocol (UDP) – Transmission Control Protocol (TCP) – Congestion Control – Quality of services (QOS) – Integrated Service

Unit-5
Teaching Hours:9
IEEE 802.11 WIRELESS LAN ? MAC & NETWORK LAYER
 

IEEE 802.11––  Architecture, Types of stations, 802.11 MAC- DCF, PCF, Hidden Node Problem, RTS,CTS, 802.11 Frame Format, Adhoc Routing Protocols – Proactive Routing, OLSR, Reactive Routing, AODV, Multipath Routing.

Text Books And Reference Books:

T1. Behrouz A. Foruzan, “Data communication and Networking”,5th edition , Tata McGraw-Hill, 2012

Essential Reading / Recommended Reading

R1. James .F. Kurouse & W. Rouse, “Computer Networking: A Topdown Approach Featuring”, 7th edition,Pearson Education,2016

R2. Larry L.Peterson & Peter S. Davie, “COMPUTER NETWORKS”, Harcourt Asia Pvt. Ltd., 5th  Edition,2011

R3. Andrew S. Tannenbaum, “Computer Networks”, PHI, 5th  Edition, 2016

R4. William Stallings, “Data and Computer Communication”, 8th  Edition, Pearson Education, 2013

R5. Azzedine Boukerche “Algorithms and Protocols for Wireless, Mobile AdHoc Networks”, Wiley-IEEE Press, 2008

Evaluation Pattern

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.

ECHO441CS - INTRODUCTION TO BLOCKCHAIN (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:12
Max Marks:100
Credits:4

Course Objectives/Course Description

 

The students should be able to understand a broad overview of the essential concepts of blockchain technology.

Course Objectives: 

  1. Understanding the concepts and the various terminologies in blockchain. 
  2. Familiarizing the various types of algorithms used in distributed computing.
  3. Understanding the workings of blockchain and the mining process.
  4.  Analyzing the various applications of blockchain technologies.
  5. Analyzing the security and privacy issues in the blockchain.

Course Outcome

1: Explain the concepts of Distributed systems, and the fundamentals and types of blockchain

2: Illustrate the various techniques in distributed computing in connection with the crypto primitives

3: Infer the operation of blockchain, the various architectures and structures used in it and essential components in Blockchain 1.0

4: Illustrate the various applications of blockchain technologies and components of Blockchain 2.0

5: Analyse the security issues in blockchain technology

Unit-1
Teaching Hours:12
Introduction
 

Distributed DBMS – Limitations of Distributed DBMS, Introduction to Block chain – History, Definition, Distributed Ledger, Blockchain Categories – Public, Private, Consortium, Blockchain Network and Nodes, Peer-to-Peer Network, Mining Mechanism, Generic elements of Blockchain, Features of Blockchain, and Types of Blockchain

Unit-2
Teaching Hours:12
Basic Distributed Computing & Crypto primitives
 

Atomic Broadcast, Consensus, Byzantine Models of Fault tolerance Hash functions, Puzzle friendly Hash, Collison resistant hash, digital signatures, public key crypto, verifiable random functions, Zero-knowledge systems.

Unit-3
Teaching Hours:12
Blockchain 1.0
 

Operation of Bitcoin Blockchain, Blockchain Architecture – Block, Hash, Distributer P2P, Structure of Blockchain- Consensus mechanism: Proof of Work (PoW), Proof of Stake (PoS), Byzantine Fault Tolerance (BFT), Proof of Authority (PoA) and Proof of Elapsed Time (PoET)

Unit-4
Teaching Hours:12
Blockchain 2.0
 

Ethereum and Smart Contracts, The Turing Completeness of Smart Contract Languages and verification challenges, Using smart contracts to enforce legal contracts, comparing Bitcoin scripting vs. Ethereum Smart Contracts

 

Unit-5
Teaching Hours:12
Privacy, Security issues in Blockchain
 

 Pseudo-anonymity vs. anonymity, Zcash and Zk-SNARKS for anonymity preservation, attacks on Blockchains – such as Sybil attacks, selfish mining, 51% attacks - -advent of algorand, and Sharding based consensus algorithms to prevent these

 

Text Books And Reference Books:
  1. Imran Bashir, “Mastering Blockchain: Distributed Ledger Technology, decentralization, and smart contracts explained”, 2nd Edition, Packt Publishing Ltd, March 2018.
  2. Bellaj Badr, Richard Horrocks, Xun (Brian) Wu, “Blockchain By Example: A developer's guide to creating decentralized applications using Bitcoin, Ethereum, and Hyperledger”, Packt Publishing Limited, 2018. 
Essential Reading / Recommended Reading
  1. Andreas M. Antonopoulos , “Mastering Bitcoin: Unlocking Digital Cryptocurrencies”, O’Reilly Media Inc, 2015.
  2. Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller and Steven Goldfeder, “Bitcoin and Cryptocurrency Technologies: A Comprehensive Introduction”, Princeton University Press, 2016.

 

Evaluation Pattern

Evaluation Pattern:

CIA-1 Evaluated out of

CIA-2 Evaluated out of

CIA-3 Evaluated out of

Total CIA Marks Reduced to

Attendance

ESE

ESE Reduced to

Total

20 Marks

50 Marks

20 Marks

45 Marks

5 Marks

100 Marks

50 Marks

100 Marks

ELC431P - OBJECT ORIENTED PROGRAMMING (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 presents the concept of object oriented programming and also introduces the concept in C++ . The students will be familiarized with concepts like data abstraction, polymorphism and inheritance.  

Course Outcome

CO1: Write Java programs using the object oriented concepts - classes, objects, constructors, data hiding, inheritance and polymorphism [L3]

CO2: Utilise datatypes, operators, control statements, built in packages & interfaces, Input/ Output Streams and Files in Java to develop programs[L3]

CO3: Illustrate how robust programs can be written in Java using exception handling mechanism[L2]

CO4: Write application programs in Java using multithreading and database connectivity [L3]

CO5: Write Graphical User Interface based application programs by utilising event handling features and Swing in Java [L3]

Unit-1
Teaching Hours:9
INTRODUCTION
 

Approaches to Software Design - Functional Oriented Design, Object Oriented Design, Case Study of Automated Fire Alarm System. Object Modeling Using Unified Modeling Language (UML) – Basic Object Oriented concepts, UML diagrams, Use case model, Class diagram, Interaction diagram, Activity diagram, State chart diagram. Introduction to Java - Java programming Environment and Runtime Environment, Development Platforms -Standard, Enterprise. Java Virtual Machine (JVM), Java compiler, Bytecode, Java applet, Java Buzzwords, Java program structure, Comments, Garbage Collection, Lexical Issues

Unit-2
Teaching Hours:9
CORE JAVA FUNDAMENTALS
 

Primitive Data types - Integers, Floating Point Types, Characters, Boolean. Literals, Type Conversion and Casting, Variables, Arrays, Strings, Vector class. Operators - Arithmetic Operators, Bitwise Operators, Relational Operators, Boolean Logical Operators, Assignment Operator, Conditional (Ternary) Operator, Operator Precedence. Control Statements - Selection Statements, Iteration Statements and Jump Statements. Object Oriented Programming in Java - Class Fundamentals, Declaring Objects, Object Reference, Introduction to Methods, Constructors, this Keyword, Method Overloading, Using Objects as Parameters, Returning Objects, Recursion, Access Control, Static Members, Final Variables, Inner Classes, Command Line Arguments, Variable Length Arguments. Inheritance - Super Class, Sub Class, The Keyword super, protected Members, Calling Order of Constructors, Method Overriding, the Object class, Abstract Classes and Methods, using final with Inheritance

Unit-3
Teaching Hours:9
PRIMARY FEATURES OF JAVA
 

Packages and Interfaces - Defining Package, CLASSPATH, Access Protection, Importing Packages, Interfaces. Exception Handling - Checked Exceptions, Unchecked Exceptions, try Block and catch Clause, Multiple catch Clauses, Nested try Statements, throw, throws and finally. Input/Output - I/O Basics, Reading Console Input, Writing Console Output, PrintWriter Class, Object Streams and Serialization, Working with Files

Unit-4
Teaching Hours:9
ADVANCED JAVA FEATURES
 

Java Library - String Handling – String Constructors, String Length, Special String Operations - Character Extraction, String Comparison, Searching Strings, Modifying Strings, using valueOf(), Comparison of StringBuffer and String. Collections framework - Collections overview, Collections Interfaces- Collection Interface, List Interface. Collections Class – ArrayList class. Accessing a Collection via an Iterator. Event handling - Event Handling Mechanisms, Delegation Event Model, Event Classes, Sources of Events, Event Listener Interfaces, Using the Delegation Model. Multithreaded Programming - The Java Thread Model, The Main Thread, Creating Thread, Creating Multiple Threads, Synchronization, Suspending, Resuming and Stopping Threads

Unit-5
Teaching Hours:9
GRAPHICAL USER INTERFACE AND DATABASE SUPPORT OF JAVA
 

Swings fundamentals - Swing Key Features, Model View Controller (MVC), Swing Controls, Components and Containers, Swing Packages, Event Handling in Swings, Swing Layout Managers, Exploring Swings –JFrame, JLabel, The Swing Buttons, JTextField. Java DataBase Connectivity (JDBC) - JDBC overview, Creating and Executing Queries – create table, delete, insert, select

Text Books And Reference Books:

T1. Herbert Schildt, Java: The Complete Reference, 8/e, Tata McGraw Hill, 2011.

T2. Rajib Mall, Fundamentals of Software Engineering, 4th edition, PHI, 2014

T3. Paul Deitel, Harvey Deitel, Java How to Program, Early Objects 11th Edition, Pearson, 2018

Essential Reading / Recommended Reading

R1. Y. Daniel Liang, Introduction to Java Programming, 7/e, Pearson, 2013

R2. Nageswararao R., Core Java: An Integrated Approach, Dreamtech Press, 2008

R3. Flanagan D., Java in A Nutshell, 5/e, O'Reilly, 2005

R4. Barclay K., J. Savage, Object Oriented Design with UML and Java, Elsevier, 2004

R5. Sierra K., Head First Java, 2/e, O'Reilly, 2005

R6. Balagurusamy E., Programming JAVA a Primer, 5/e, McGraw Hill, 2014

Evaluation Pattern

As per University Norms

ELC432 - ARTIFICIAL INTELLIGENCE (2022 Batch)

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

Course Objectives/Course Description

 

This course aims to introduce artificial intelligence by knowledge representation using semantic networks and rules, concepts of logic in artificial intelligence, concepts of planning and learning with an introduction of the expert systems.  

Course Outcome

CO1: Formulate an efficient problem space for a problem in artificial intelligence

CO2: Select a search algorithm for a problem and characterize its time and space complexities

CO3: Understand the concepts of knowledge representation using an appropriate technique

CO4: Apply AI techniques to solve problems of Game Playing, Expert Systems, Machine Learning and Natural Language Processing

CO5: Explain expert systems based on architecture, roles and knowledge acquisition.

Unit-1
Teaching Hours:9
INTRODUCTION
 

Introduction, History, Intelligent Systems, Foundations of AI, Sub areas of AI, Applications. Problem Solving – State-Space Search and Control Strategies: Introduction, General Problem Solving, Characteristics of Problem, Exhaustive Searches, Heuristic Search Techniques, Iterative-Deepening A*, Constraint Satisfaction. Game Playing, Bounded Look-ahead Strategy and use of Evaluation Functions, Alpha-Beta Pruning. 

Unit-2
Teaching Hours:9
KNOWLEDGE REPRESENTATION AND LOGIC
 

Logic Concepts and Logic Programming: Introduction, Propositional Calculus, Propositional Logic, Natural Deduction System, Axiomatic System, Semantic Tableau System in Propositional Logic, Resolution Refutation in Propositional Logic, Predicate Logic, Logic Programming. Knowledge Representation: Introduction, Approaches to Knowledge Representation, Knowledge Representation using Semantic Network, Extended Semantic Networks for KR, Representing Knowledge using rules – Rules based deduction system, Knowledge Representation using Frames

Unit-3
Teaching Hours:9
REASONING UNDER UNCERTAINITY
 

Introduction to uncertain knowledge review of probability – Baye’s Probabilistic inferences and Dempster Shafer theory –Heuristic methods – Symbolic reasoning under uncertainty- Statistical reasoning – Fuzzy reasoning – Temporal reasoning- Non monotonic reasoning.

Unit-4
Teaching Hours:9
PLANNING AND LEARNING
 

Planning - Introduction, Planning in situational calculus - Representation for planning – Partial order planning algorithm- Learning from examples- Discovery as learning – Learning by analogy – Explanation based learning –Introduction to Neural nets – Genetic Algorithms

Unit-5
Teaching Hours:9
EXPERT SYTEMS
 

Expert Systems – Architecture Of Expert Systems, Roles Of Expert Systems – Knowledge Acquisition –Meta Knowledge, Heuristics. Typical Expert Systems – MYCIN, DART, XOON, Expert Systems Shells.

Text Books And Reference Books:

T1.Saroj Kaushik. Artificial Intelligence. Cengage Learning. 2011

T2. Patrick Henry Winston,” Artificial Intelligence”, Addison Wesley, Third edition, 2010

T3. Kevin Night And Elaine Rich, Nair B., “Artificial Intelligence (SIE)”, McGraw Hill- 2008

Essential Reading / Recommended Reading

R1. George F Luger, Artificial Intelligence, Pearson Education, 6th edition,2009

R2. Engene Charniak and Drew Mc Dermott,” Introduction to Artificial intelligence, Addison Wesley, 2009

R3. Nils J. Nilsson,”Principles of Artificial Intelligence“, Narosa Publishing House, 2000

Evaluation Pattern

As per University norms

ELC433 - SIGNALS AND SYSTEMS (2022 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 the mathematical representation of signals and systems using various transforms such as laplace, fourier and z-transforms. The course is designed to make the students familiar with the signals and their variations so that the fundamental of electronics engineering is well placed out. 

Course Outcome

CO1: Understand the relation among transfer function, convolution and the impulse response

CO2: Understand the relationship between the stability and causality of systems and the region of convergence of their Laplace transforms

CO3: Express periodic signals in terms of Fourier series and represent an arbitrary signal in terms of a fourier transform

CO4: Apply the Z- transform of continuous-time and discrete-time signals for stability analysis

CO5: Explain basics of signals and systems to find the response of LTI system using convolutio

Unit-1
Teaching Hours:9
INTRODUCTION
 

Definition, types of signals and their representations: continuous-time/discrete-time, periodic/non-periodic, even/odd, energy/power, deterministic/ random, one dimensional/ multidimensional; commonly used signals (in continuous-time as well as in discrete-time): unit impulse, unit step, unit ramp (and their interrelationships), exponential, rectangular pulse, sinusoidal; operations on continuous-time and discrete-time signals (including transformations of independent variables)

Unit-2
Teaching Hours:9
LAPLACE TRANSFORM
 

One-sided LT of some common signals, important theorems and properties of LT, inverse LT, solutions of differential equations using LT, Bilateral LT, Regions of convergence (ROC

Unit-3
Teaching Hours:9
FOURIER TRANSFORM
 

Definition, conditions of existence of FT, properties, magnitude and phase spectra, Some important FT theorems, Parseval’s theorem, Inverse FT, relation between LT and FT, Discrete time Fourier transform (DTFT), inverse DTFT, convergence, properties and theorems, Comparison between continuous time FT and DTFT.

Unit-4
Teaching Hours:9
LINEAR TIME INVARIANT SYSTEMS
 

Continuous Time Systems: Linear Time invariant Systems and their properties. Differential equation & Block diagram representation, Impulse response, Convolution integral, Frequency response (Transfer Function), Fourier transforms analysis. Discrete Time System: Difference equations, Block diagram representation, Impulse response, Convolution sum, MATLAB tutorials

Unit-5
Teaching Hours:9
LINEAR TIME INVARIANT SYSTEMS
 

Continuous Time Systems: Linear Time invariant Systems and their properties. Differential equation & Block diagram representation, Impulse response, Convolution integral, Frequency response (Transfer Function), Fourier transforms analysis. Discrete Time System: Difference equations, Block diagram representation, Impulse response, Convolution sum, MATLAB tutorials

Text Books And Reference Books:

T1. P. Ramakrishna Rao, `Signal and Systems’ 2008 Ed., Tata McGraw Hill, New DelhIi.

T2. Signals, Systems & Communications - B.P. Lathi, BS Publications, 2003

Essential Reading / Recommended Reading

R1. Signals & Systems - Simon Haykin and Van Veen, Wiley, 2nd Edition

R2. Principles of Linear Systems and Signals, BP Lathi, Oxford University Press, 2015

R3. Fundamentals of Signals and Systems- Michel J. Robert, MGH International Edition, 2008

 

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

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

 

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

CSOE561E04 - PYTHON FOR ENGINEERS (2021 Batch)

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

Course Objectives/Course Description

 

Specifically, the course has the following objectives. By the end of the course, students will be able to:

       Develop a working knowledge for how computers operate and how computer programs are executed.

       Evolve critical thinking and problem-solving skills using an algorithmic approach.

       Learn about the programmer’s role in the software development process.

            Translate real-world issues into computer-solvable problems.

Course Outcome

CO1: Demonstrate the basic methods of formatting, outputting data, kinds of data, operators and variables.

CO2: Interpret with the concepts of Boolean values, utilization of loops and operators.

CO3: Experiment with functions, passing arguments and data processing.

CO4: Illustrate the concept of modules, exceptions, strings and lists.

CO5: Apply the fundamentals of OOP and its implementation.

Unit-1
Teaching Hours:9
INTRODUCTION
 

Introduction to Python and computer programming: Programming – absolute basics, Python – a tool, not a reptile, First program, Python literals, Operators – data manipulation tools, Variables

Unit-2
Teaching Hours:9
CONDITIONAL STATEMENTS LOOPING AND ARRAY
 

Making decisions in Python, Python's loops, Logic and bit operations in Python, Lists – collections of data, Sorting simple lists – the bubble sort algorithm, Lists – some more details, Lists in advanced applications

Unit-3
Teaching Hours:9
FUNCTIONS
 

Writing functions in Python, How functions communicate with their environment, Returning a result from a function, Scopes in Python. Creating functions, Tuples and dictionaries

Unit-4
Teaching Hours:9
MODULES
 

Using modules, Some useful modules, Package, Errors, The anatomy of an exception, Some of the most useful exceptions, Characters and strings vs. computers, The nature of Python's strings, String methods, Strings in action.

Unit-5
Teaching Hours:9
FUNDAMENTALS OF OOP
 

Basic concepts of object programming, A short journey from the procedural to the object approach, Properties, Methods, Inheritance – one of object programming foundations, Generators and closures, Processing files, Working with real files.

Text Books And Reference Books:

T1. Eric Matthes,  “Python Crash Course”, 2nd Edition: A Hands-On, Project-Based Introduction to Programming, No Starch Press, Inc, 2016

T2. Paul Barry, “Head first Python”, 2nd Edition, O’Reilly, 2017.

Essential Reading / Recommended Reading

R1: Paul Barry,Head First Python: A Brain-Friendly Guide”, Shroff/O'Reilly; Second edition (1 December 2016)

R2: Martin C. Brown,”Python: The Complete Reference”, McGraw Hill Education; Forth edition (20 March 2018)

Evaluation Pattern

CIA Marks : 50

ESE Marks : 50

CSOE561E05 - BASICS OF MACHINE LEARNING (2021 Batch)

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

Course Objectives/Course Description

 

Course objectives: 

•          To understand the need for machine learning

•          To discover supervised and unsupervised learning paradigms of machine learning

•          To learn various machine learning techniques

•          To design suitable machine learning algorithms for solving problems

Course Outcome

CO 1: Describe various supervised learning methods

CO 2: Discuss various unsupervised learning methods.

CO 3: Explain the basics of neural networks and back propagation algorithm for problem solving.

CO 4: Describe the usage of genetic algorithms in problem solving.

CO 5: Use the concept of Bayesian theory to machine learning.

Unit-1
Teaching Hours:9
Unit-1 SUPERVISED LEARNING
 

Basic methods: Distance-based methods, Nearest-Neighbours, Decision Trees, Naive Bayes.         Linear models: Linear Regression, Logistic Regression, Generalized Linear Models.Support Vector Machines.

Unit-2
Teaching Hours:9
Unit-2 UNSUPERVISED LEARNING
 

Clustering: K-means/Kernel K-means,Dimensionality Reduction: PCA and kernel PCA,         Matrix Factorization and Matrix Completion.

Unit-3
Teaching Hours:9
Unit-3 NEURAL NETWORKS
 

Neural Network Representation – Problems – Perceptrons – Multilayer Networks and Back Propagation Algorithms – Advanced Topics.

Unit-4
Teaching Hours:9
Unit-4 BAYESIAN AND COMPUTATIONAL LEARNING
 

Bayes Theorem – Concept Learning – Maximum Likelihood – Minimum Description Length Principle – Bayes Optimal Classifier – Gibbs Algorithm – Naïve Bayes Classifier – Bayesian Belief Network – EM Algorithm.

Unit-5
Teaching Hours:9
Unit-5 INSTANCE-BASED, ANALYTICAL LEARNING AND INDUCTIVE BASED LEARNING