Syllabus for
Bachelor of Technology (Artificial Intelligence and Machine Learning)
Academic Year  (2023)

The objective of this course is to describe the fundamental concepts of
linear algebra along with set theory, probability theory, random process, queuing theory to
support the graduate coursework and research

Block Matrices, Norms, Rank, Least Squares, Orthogonality, Gram-Schmidt, Matrix norms, SVD, SVD geometry and PCA 

Axioms of Probability, Conditional Probability, Total Probability, Baye‘s Theorem, Random variable, Probability mass function, Probability Density functions, Properties, Moments, Moment generating functions and their properties.

Binomial, Poisson , Geometric, Negative binomial, Uniform, Exponential, Gamma, Weibull and normal distributions and their properties – Functions of Random Variables.

Multidimensional random variable: Joint distribution – Marginal and conditional distribution - Co-variance – Correlation and Regression – Transformation of Random Variables – Central Limit Theorem

2. E. Kreyszig, Advanced engineering mathematics , John Wiley publications.

ESE-100

To study  syntax, semantics, and the runtime environment of Python and R programming language. To be familiarized with universal computer programming concepts like data types, containers. To be familiarized with general computer programming concepts like conditional execution, loops & functions.  Since R, is a popular statistical programming language students will learn data reading and its manipulation and be familiar with data analysis.

Conceptual introduction: topics in computer science, algorithms; modern computer systems: hardware architecture, data representation in computers, software and operating system;

Python; basic syntax, interactive shell, editing, saving, and running a script, Data types, understanding error messages, Conditions, boolean logic, logical operators

Manipulating files and directories, os and sys modules, reading/writing text and numbers from/to a file, creating and reading a formatted file (csv or tab-separated). String manipulations, slicing a string, strings and number system, Lists, tuples, and dictionaries

Simple Graphics and Image Processing: “turtle” module; simple 2d drawing - colors, shapes; digital images, image file formats, image processing Simple image manipulations with 'image' module.

Searching, Sorting, and Complexity Analysis

Lists, R– matrices, R– factors, -Factors in Data Frame, Changing the Order of Levels, Generating Factor Levels, R – data frames.

Common Functions Used with Factors- The tapply() Function - The split() Function -The by() Function - Working with Tables.

ESE-30

To study the basics of digital circuits and learn methods and fundamental concepts used in the design of digital systems as well as   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

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

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

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.

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

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

ESE-30

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.  

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. 

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

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

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

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

ESE-50

To understand  the fundamental concepts and principles of signals and systems. To demonstrate spectral analysis of continuous time periodic and aperiodic signals using  Fourier and Laplace methods. Study about the characterization of total response, impulse response and frequency response of continuous and digital systems. To interpret discrete time signal by Discrete Time Fourier transforms and Z transform.  To analyse and characterization of total response, impulse response and frequency response of linear time invariant systems.

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)

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. Sampling theorem

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)

One sided and Bilateral Z- transforms, ZT of some common signals, ROC, Properties and theorems, solution of difference equations using one-sided ZT, s- to z-plane mapping

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

ESE-50

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

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

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

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.

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

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

Identify, formulate, research literature, and analyse complex engineering

problems reaching substantiated conclusions using first principles of mathematics, natural

sciences, and engineering sciences.

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

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

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

ESE-50

To understand the basics of multivariate calculus and to define an objective function and constraint functions in terms of design variables, and then state the optimization problem without and with constraints. To explain graph theory and the associated  algorithms for  graph colouring and trees 

Functions, Scalar derivative, rules of differentiation, partial derivatives, Gradient, directional derivative. Vector and matrix calculus: How to find derivative of {scalar-valued, vector- valued} function with respect to a {scalar, vector}

Objective function, Constraints and Constraint surface; Formulation of design problems as mathematical programming problems. Classification of optimization problems Optimization using Calculus: Convexity and concavity of functions of one and two

variables, local/global maxima and minima, saddle point, Gradient vectors, Lagrangian function, KKT method.

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

ESE-100

This course provides an introduction to basic skill set required in the fast expanding field of machine learning. Students will learn relevant basics in machine learning such as regression, clustering and classification. In addition, this course introduces advanced Python programming as a standard and common language for machine learning. This course is proposed to meet the growing business needs of individuals skilled in artificial intelligence, data analytics, statistical programming and other software skills. The proposed course will combine theory and practice to enable the student to gain the necessary knowledge to compete in the ever changing work environment

Types of machine learning, Designing Learning systems, Perspectives and Issues, Concept Learning, Version Spaces and Candidate Elimination Algorithm, Inductive bias.

Classification and Regression - Generalization, Overfitting, and Underfitting-Relation of Model Complexity to Dataset Size -Supervised Machine Learning Algorithms

K- Nearest Neighbour Learning, Locally Weighted Regression, Radial Basis Functions, Case-Based Reasoning.

Sequential Covering Algorithms, Learning Rule Sets, Learning First Order Rules, Learning Sets of First Order Rules.

Bayes Theorem, Bayes Theorem Concept Learning, Maximum Likelihood, Minimum Description Length Principle, Bayes Optimal Classifier, Gibbs Algorithm, Naïve Bayes Classifier.

ESE-30

• Analyze and Compute FFT of a discrete time signal.
• Design the various FIR filter techniques.
• Design the various IIR filter techniques.
• Analyze the finite word length effects in signal processing.
• Learn the fundamentals of digital signal processors.

Introduction to DFT – Efficient computation of DFT- Properties of DFT – FFT algorithms – Radix-2 FFT algorithms – Decimation in Time – Decimation in Frequency algorithms –sectioned convolution- overlap add method- overlap save method.

Linear phase filters-Frequency response of linear phase FIR filters-Fourier series method of designing FIR filters-Windowing techniques for design of linear phase FIR filters: Rectangular- Hamming- Hanning -Blackman windows - Gibbs phenomenon –principle of frequency sampling technique- FIR Filter Realization-Direct form, Cascade ,Linear phase FIR realization.

Review of design of analogue Butterworth and Chebyshev Filters- Design of IIR digital filters using impulse invariance technique –bilinear transformation – pre warping –Frequency transformation in digital domain – IIR Filter Realization - Direct form I, Direct form II, cascade and parallel

Introduction to DSP Architecture – Dedicated MAC unit - Features of C6X Processor - Internal Architecture - Functional Units and Operation - Addressing Modes

2. S. K. Mitra- “Digital Signal Processing- A Computer based approach”, TataMc-Graw-Hill, 2001, New Delhi.

3. B. Venkataramani & M.Bhaskar, Digital Signal Processor Architecture-Programming and Application, Tata Mc-GrawHill 2002

ESE-100

The objective of this course is to impart knowledge about the engineering aspects of robotics and their applications and understand about the different sensors used in robotics

Sensor: Contact and Proximity, Position, Velocity, Force, Tactile etc.
Introduction to Cameras, Camera calibration, Geometry of Image formation, Euclidean/Similarity/Affine/Projective transformations, Vision applications in robotics

Robot anatomy - Definition, law of robotics. Types and components of a robot, Classification of robots, Kinematics systems; Definition of mechanisms and manipulators, Degrees of Freedom.

Kinematic Modelling: Translation and Rotation Representation, Coordinate transformation, DH parameters, Forward and inverse kinematics, Jacobian, Singularity, Statics Dynamic Modelling: Forward and inverse dynamics, Equations of motion using Euler-Lagrange formulation, Newton Euler formulation.

Applications in unmanned systems, defence, medical, industries, etc., Robotics and Automation for Industry 4.0, Robot safety and social robotics. 

2. Thomas Braunl, “Embedded Robotics”, Second Edition, Springer, 2006.

3. Sensor & transducers, D. Patranabis, 2nd edition, PHI

2. Instrument transducers, H.K.P. Neubert, Oxford University press.

ESE-100

Fundamentals of algorithm analysis, Space and time complexity of an algorithm, Types of asymptotic notations and orders of growth, Algorithm efficiency – best case, worst case, average case, Analysis of non-recursive and recursive algorithms.

Array- 1D and 2D array, Stack - Applications of stack: Expression Evaluation - Conversion of Infix to postfix and prefix expression. Queue - Types of Queues: Circular Queue, Double Ended Queue (deQueue). List - Singly linked lists – Doubly linked lists - Circular linked lists, Applications -Polynomial Addition/Subtraction

Sorting Algorithms: Basic concepts, Bubble Sort, Insertion Sort, Selection Sort, Quick Sort, Shell Sort, Heap Sort, Merge Sort, External Sorting, Internal Sorting. Searching: Linear Search, Binary Search. 

Terminology, Binary Tree – Terminology and Properties, Tree Traversals, Expression Trees – Binary Search Trees – operations in BST – insertion, deletion, Searching. AVL Trees-Insertion, deletion and Rotation in AVL Trees 

Basic definition and Terminology – Representation of Graph – Graph Traversal: Breadth First Search (BFS), Depth First Search (DFS) - Minimum Spanning Tree: Prim's, Kruskal's- Single Source Shortest Path: Dijkstra’s Algorithm. Hashing: Introduction, open hashing-separate chaining, closed hashing - linear probing, quadratic probing, double hashing, random probing, rehashing

2. Ellis Horowitz, S. Sahni, Freed, “Fundamentals of Data Structures in C”,2nd edition,2015.

2. Seymour Lipschutz, Data Structures, Schaum's Outlines Series, Tata McGraw-Hill

3. Vishal Goyal, Lalit Goyal and Pawan Kumar, Simplified approach to Data Structures, Shroff publications and Distributors.

ESE- 100

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.

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.

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

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.

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)

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

 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

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.   

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

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

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

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

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.

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

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

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

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.

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

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 

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

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.