Abhi PYQ

6th Semester Syllabus

B. Tech CSE (AI)

Credits Table

Course Title L T P Credits
Machine Learning [151601] 3 1 0 4
Automata Theory and Compiler Design [151602] 3 0 0 3
Ad hoc & Network Sensors [151603] 3 0 0 3
AI and Ethics [151604] 1 0 0 1
Constitution of India [151605] 3 0 0 0
Program Elective Course-II [1516XX] 3 0 0 3
Program Elective Course-III [1516XX] 3 0 0 3
Machine Learning Lab [151601P] 0 0 4 2
Ad hoc & Network Sensors Lab [151603P] 0 0 4 2
NPTEL Course-II Lab [151606P] 0 0 4 2
TOTAL 23

Theory Subjects

Lab Subjects

Machine Learning [151601]

  • Unit 1.0: Introduction
    • Basic definitions
    • Linear Algebra
    • Statistical learning theory
    • Types of learning
    • Hypothesis space and Inductive bias
    • Evaluation and cross validation
    • Optimization
  • Unit 2.0: Statistical Decision Theory and Learning
    • Statistical Decision Theory
    • Bayesian Learning (ML, MAP, Bayes estimates, Conjugate priors)
    • Linear Regression
    • Ridge Regression
    • Lasso
    • Principal Component Analysis
    • Partial Least Squares
  • Unit 3.0: Linear Classification and Advanced Models
    • Linear Classification
    • Logistic Regression
    • Linear Discriminant Analysis
    • Quadratic Discriminant Analysis
    • Perceptron
    • Support Vector Machines + Kernels
    • Artificial Neural Networks + Back Propagation
    • Decision Trees
    • Bayes Optimal Classifier
    • Naive Bayes
  • Unit 4.0: Hypothesis testing and Ensemble Methods
    • Hypothesis testing
    • Ensemble Methods
    • Bagging Adaboost Gradient Boosting
  • Unit 5.0: Clustering
    • Clustering
    • K-means
    • K-medoids
    • Density-based Hierarchical
    • Spectral
  • Unit 6.0: Advanced Learning Theory
    • Expectation Maximization
    • GMMs
    • Learning theory Intro to Reinforcement Learning
    • Bayesian Networks

Text/Reference Books:

  1. Machine Learning. Tom Mitchell. First Edition, McGraw-Hill, 1997
  2. Introduction to Machine Learning Edition 2, by Ethem Alpaydin.
  3. J. Shavlik and T. Dietterich (Ed), Readings in Machine Learning, Morgan Kaufmann, 1990.
  4. P. Langley, Elements of Machine Learning, Morgan Kaufmann, 1995.
  5. Understanding Machine Learning. Shai Shalev-Shwartz and Shai Ben-David. Cambridge University Press. 2017. [SS-2017]
  6. The Elements of Statistical Learning. Trevor Hastie, Robert Tibshirani and Jerome Friedman. Second Edition. 2009. [TH-2009]

Automata Theory & Compiler Design [151602]

  • Unit 1.0: Formal Language and Regular Expressions
    • Formal Language and Regular Expressions Languages
    • Definition Languages regular expressions
    • Finite Automata - DFA
    • NFA
    • Conversion of regular expression to NFA
    • NFA to DFA
  • Unit 2.0: Applications and Context Free Grammars
    • Applications of Finite Automata to lexical analysis
    • Lex tools
    • Context Free grammars and parsing: Context free grammars
    • Derivation
    • Parse trees
    • Ambiguity LL(K) grammars and LL(1) parsing
  • Unit 3.0: Bottom up parsing and Semantics
    • Bottom up parsing handle pruning LR Grammar Parsing
    • LALR parsing
    • Parsing ambiguous grammars
    • YACC programming specification
    • Semantics: Syntax directed translation
    • S-attributed and L-attributed grammars
    • Intermediate code abstract syntax tree
    • Translation of simple statements and control flow statements
  • Unit 4.0: Context Sensitive features and Type checking
    • Context Sensitive features - Chomsky hierarchy of languages and recognizers
    • Type checking
    • Type conversions
    • Equivalence of type expressions
    • Overloading of functions and operations
  • Unit 5.0: Run time storage and Code optimization
    • Run time storage: Storage organization
    • Storage allocation strategies scope access to now local names
    • Parameters
    • Language facilities for dynamics storage allocation
    • Code optimization: Principal sources of optimization
    • Optimization of basic blocks
    • Peephole optimization
    • Flow graphs
    • Data flow analysis of flow graphs
  • Unit 6.0: Code generation
    • Code generation Machine dependent code generation
    • Object code forms
    • Generic code generation algorithm
    • Register allocation and assignment
    • Using DAG representation of Blocks

Text/Reference Books:

  1. Introduction to Theory of computation. Sipser, 2nd Edition, Thomson.
  2. Compilers Principles, Techniques and Tools Aho, Ullman, Ravisethi, Pearson Education.
  3. Modern Compiler Construction in C, Andrew W.Appel Cambridge University Press.
  4. Compiler Construction, LOUDEN, Thomson.
  5. Elements of Compiler Design, A. Meduna, Auerbach Publications, Taylor and Francis Group.
  6. Principles of Compiler Design, V. Raghavan, TMH.
  7. Engineering a Compiler, K. D. Cooper, L. Torczon, ELSEVIER.

Ad hoc & Network Sensors [151603]

  • Unit 1.0: Introduction to Ad Hoc and Sensor Networks
    • Characteristics of ad hoc wireless networks
    • Applications of ad hoc networks
    • Challenges in ad hoc networks
    • Wireless sensor networks (WSN) - Characteristics and applications
    • Design issues in WSN
    • Sensor network architecture - Layered architecture
    • Cross-layer design
  • Unit 2.0: MAC Protocols for Ad Hoc and Sensor Networks
    • Fundamentals of MAC design
    • Issues in designing MAC protocols
    • MAC protocols for ad hoc networks Contention-based protocols (Aloha, CSMA, MACA, MACAW)
    • Scheduling-based MAC protocols
    • MAC protocols for WSN - S-MAC, T-MAC, B-MAC, X-MAC
    • Energy-efficient MAC protocols
  • Unit 3.0: Routing Protocols in Ad Hoc and Sensor Networks
    • Challenges in routing
    • Proactive vs. Reactive routing
    • Ad hoc routing protocols - AODV, DSR, DSDV, OLSR
    • Hybrid routing (ZRP)
    • Hierarchical routing
    • Geographic routing
    • Routing protocols for WSN Flooding, SPIN, LEACH, TEEN
    • Directed diffusion
    • Geographic and Energy-Aware Routing (GEAR)
  • Unit 4.0: Transport and Energy Management in Wireless Sensor Networks
    • Issues in transport protocols
    • TCP over ad hoc networks
    • Transport protocols for WSN - CODA, RMST, PSFQ, ESRT
    • Energy-efficient routing in WSN
    • Data aggregation
    • Clustering techniques for WSN
    • Energy harvesting in sensor networks
    • Sleep-wake scheduling algorithms
  • Unit 5.0: Localization, Synchronization, and Data Dissemination in WSN
    • Localization techniques - GPS-based localization
    • Range-based localization (RSSI, TOA, TDOA, AOA)
    • Range-free localization (Centroid, DV-Hop, APIT)
    • Time synchronization in WSN - RBS, TPSN
    • Data dissemination and query processing in WSN
    • Mobile sink-based data collection
  • Unit 6.0: Security and Emerging Trends in Ad Hoc and Sensor Networks
    • Security issues in ad hoc and sensor networks
    • Attack models - Eavesdropping, Sybil attack, Blackhole, Wormhole
    • Intrusion detection in WSN
    • Secure routing in ad hoc networks
    • Privacy-preserving techniques
    • Emerging trends Mobile ad hoc networks (MANETs)
    • Vehicular ad hoc networks (VANETS)
    • Cognitive radio sensor networks (CRSN)
    • AI/ML applications in WSN

Text/Reference Books:

  1. C. Siva Ram Murthy, B.S. Manoj, Ad Hoc Wireless Networks: Architectures and Protocols, Pearson, 2004.
  2. Feng Zhao, Leonidas Guibas, Wireless Sensor Networks: An Information Processing Approach, Elsevier, 2004.
  3. Holger Karl, Andreas Willig, Protocols and Architectures for Wireless Sensor Networks, Wiley, 2005.
  4. C. K. Toh, Ad Hoc Mobile Wireless Networks: Protocols and Systems, Pearson, 2002.
  5. Edgar H. Callaway, Wireless Sensor Networks: Architectures and Protocols, CRC Press, 2003.
  6. Thomas Haenselmann, Wireless Sensor Networks: Design Principles for Scalable Distributed Systems, Springer, 2007.
  7. Kazem Sohraby, Daniel Minoli, Taieb Znati, Wireless Sensor Networks: Technology, Protocols, and Applications, Wiley, 2007.

AI and Ethics [151604]

  • Unit 1.0: Introduction
    • Definition of morality and ethics in AI
    • AI
    • And society
  • Unit 2.0: Impact of AI
    • Impact on society
    • Impact on human psychology
    • Impact on the legal system
    • Impact on the environment and the planet
    • And Impact on trust
  • Unit 3.0: Ethical Initiatives in AI
    • International ethical initiatives
    • Ethical harms
    • And concerns
    • Case study: healthcare robots
    • Autonomous Vehicles
    • Warfare
    • And weaponization
  • Unit 4.0: AI Standards And Regulation
    • Model Process for Addressing Ethical Concerns During System Design
    • Transparency of Autonomous Systems
    • Data Privacy Process
    • Algorithmic Bias Considerations
    • Ontological Standard for Ethically Driven Robotics and Automation Systems
  • Unit 5.0: Rob ethics: Social and Ethical Implication of Robotics
    • Robotics- Ethics and Morality
    • Moral Theories-Ethics in Science and Technology
    • Ethical Issues in an ICT Society
    • Harmonization of Principles
    • Ethics and Professional Responsibility
    • Robotics Taxonomy
  • Unit 6.0: Challenges and Opportunities
    • Ethical issues in artificial intelligence
    • Societal Issues Concerning the Application of Artificial Intelligence in Medicine
    • Decision-making role in industries
    • And National and International Strategies on AI

Text/Reference Books:

  1. Eleanor Bird, Jasmin Fox-Skelly, Nicola Jenner, Ruth Larbey, Emma Weitkamp and Alan Winfield," The ethics of artificial intelligence: Issues and initiatives", EPRS | European Parliamentary Research Service Scientific Foresight Unit (STOA) PE 634.452- March 2020.
  2. Patrick Lin, Keith Abney, George A Bekey," Robot Ethics: The Ethical and Social Implications of Robotics", The MIT Press- January 2014.
  3. Towards a Code of Ethics for Artificial Intelligence (Artificial Intelligence: Foundations, Theory, and Algorithms) by Paula Boddington, November 2017.
  4. Mark Coeckelbergh," AI Ethics", The MIT Press Essential Knowledge series, April 2020.

Constitution of India [151605]

  • Unit 1.0: Introduction to Constitution
    • Meaning of the constitution law and constitutionalism
    • Historical perspective of the Constitution of India
    • Salient features and characteristics of the Constitution of India
  • Unit 2.0: Fundamental Rights and Duties
    • Scheme of the fundamental rights
    • The scheme of the Fundamental Duties and its legal status
    • The Directive Principles of State Policy - Its importance and implementation
  • Unit 3.0: Federal Structure and Government
    • Federal structure and distribution of legislative and financial powers between the Union and the States
    • Parliamentary Form of Government in India - The constitution powers and status of the President of India
  • Unit 4.0: Amendments
    • Amendment of the Constitutional Powers and Procedure
    • The historical perspectives of the constitutional amendments in India
  • Unit 5.0: Emergency Provisions and Local Self Government
    • Emergency Provisions: National Emergency
    • President Rule
    • Financial Emergency
    • Local Self Government - Constitutional Scheme in India
  • Unit 6.0: Scheme of Rights
    • Scheme of the Fundamental Right to Equality
    • Scheme of the Fundamental Right to certain Freedom under Article 19
    • Scope of the Right to Life and Personal Liberty under Article 21

Text/Reference Books:

  1. "Constitution of India" (for Competitive Exams) Published by Naidhruva Edutech Learning Solutions, Bengaluru. - 2022.
  2. "Introduction to the Constitution of India", (Students Edition.) by Durga Das Basu (DD Basu): Prentice-Hall, 2008.
  3. "Constitution of India, Professional Ethics and Human Rights" by Shubham Singles, Charles E. Haries, and et al: published by Cengage Learning India, Latest Edition - 2019.
  4. "The Constitution of India" by Merunandan K B: published by Merugu Publication, Second Edition, Bengaluru.
  5. "Samvidhana Odu" - for Students & Youths by Justice HN Nagamohan Dhas, Sahayana, kerekon.
  6. M.Govindarajan, S.Natarajan, V.S.Senthilkumar, "Engineering Ethics", Prentice-Hall, 2004.

Program Elective-II: Cloud Computing Network [151607]

  • Unit 1.0: Introduction to Cloud Computing
    • Definition and characteristics of cloud computing
    • Cloud service models (IaaS, PaaS, SaaS)
    • Deployment models (Public, Private, Hybrid, Multi-cloud)
    • Cloud computing architecture
    • Virtualization in cloud computing
    • Hypervisors (VMware, KVM, Xen)
  • Unit 2.0: Cloud Networking Basics
    • Cloud network architecture
    • Software-Defined Networking (SDN)
    • Network Functions Virtualization (NFV)
    • Virtual Private Cloud (VPC)
    • Content Delivery Networks (CDN)
    • Cloud load balancing and traffic management
  • Unit 3.0: Cloud Storage and Data Management
    • Cloud storage models (Object, Block, File storage)
    • Distributed file systems (Google File System, Hadoop HDFS)
    • Cloud database services (NoSQL, NewSQL)
    • Data consistency and replication
    • Cloud backup and disaster recovery
  • Unit 4.0: Cloud Security and Compliance
    • Cloud security challenges
    • Identity and Access Management (IAM)
    • Encryption in cloud
    • Secure cloud networking (VPN, TLS, SSL)
    • Compliance standards (ISO 27001, GDPR, HIPAA)
    • Zero Trust security in cloud environments
  • Unit 5.0: Cloud Deployment and Orchestration
    • Containerization (Docker, Kubernetes)
    • Serverless computing
    • Cloud automation (Terraform, Ansible)
    • Multi-cloud and hybrid cloud management
    • Microservices architecture in cloud
    • Edge computing and IoT integration
  • Unit 6.0: Emerging Trends and Case Studies
    • AI and Machine Learning in cloud computing
    • Blockchain for cloud security
    • Quantum computing and cloud
    • Case studies on real-world cloud deployments (AWS, Azure, Google Cloud)
    • Future trends in cloud networking

Text/Reference Books:

  1. Rajkumar Buyya, Christian Vecchiola, S. Thamarai Selvi, Mastering Cloud Computing, McGraw Hill.
  2. Thomas Erl, Ricardo Puttini, Zaigham Mahmood, Cloud Computing: Concepts, Technology & Architecture, Pearson.
  3. Anthony T. Velte, Toby J. Velte, Robert Elsenpeter, Cloud Computing: A Practical Approach, McGraw Hill.
  4. Arshdeep Bahga & Vijay Madisetti, Cloud Computing: A Hands-on Approach, Universities Press.
  5. Kai Hwang, Geoffrey Fox, Jack Dongarra, Distributed and Cloud Computing, Elsevier.
  6. George Reese, Cloud Application Architectures: Building Applications and Infrastructure in the Cloud, O'Reilly.
  7. Benedict Blundell, Docker and Kubernetes for Cloud Networking, Packt Publishing.

Program Elective-II: Distributed Computing [151608]

  • Unit 1.0: Introduction to Distributed Computing
    • Definition
    • Characteristics of distributed systems
    • Types of distributed architectures (client-server, peer-to-peer, multi-tier)
    • Distributed system models
    • Advantages and challenges
    • Design issues
  • Unit 2.0: Inter-Process Communication & Synchronization
    • Message passing mechanisms
    • Remote Procedure Call (RPC)
    • Remote Method Invocation (RMI)
    • Synchronization in distributed systems
    • Logical clocks (Lamport & Vector clocks)
    • Mutual exclusion algorithms (Ricart-Agrawala, Maekawa's algorithm)
  • Unit 3.0: Distributed Algorithms and Fault Tolerance
    • Leader election algorithms (Bully, Ring)
    • Distributed consensus (Paxos, RAFT)
    • Load balancing strategies
    • Distributed deadlock detection
    • Fault tolerance models
    • Checkpointing and recovery techniques
  • Unit 4.0: Distributed File Systems and Databases
    • Distributed file systems (NFS, AFS, Google File System)
    • Distributed databases (CAP theorem, NoSQL, Replication & Consistency models)
    • Two-phase & three-phase commit protocols
    • Cloud-based storage architectures
  • Unit 5.0: Distributed Computing Frameworks & Middleware
    • Hadoop ecosystem (HDFS, MapReduce, YARN)
    • Apache Spark
    • Distributed middleware (CORBA, JINI, Web services)
    • Edge and Fog Computing
    • Serverless computing
  • Unit 6.0: Emerging Trends and Case Studies
    • Microservices and Kubernetes
    • Blockchain in distributed environments
    • AI and ML in distributed systems
    • Internet of Things (IoT) and distributed processing
    • Case studies on real-world distributed applications (Google Spanner, Amazon DynamoDB)

Text/Reference Books:

  1. Andrew S. Tanenbaum & Maarten Van Steen, Distributed Systems: Principles and Paradigms, Pearson.
  2. George Coulouris, Jean Dollimore, Tim Kindberg, Distributed Systems: Concepts and Design, Pearson.
  3. Mukesh Singhal & Niranjan G. Shivaratri, Advanced Concepts in Operating Systems: Distributed, Database, and Multiprocessor Operating Systems, McGraw Hill.
  4. Ajay D. Kshemkalyani & Mukesh Singhal, Distributed Computing: Principles, Algorithms, and Systems, Cambridge University Press.
  5. Hagit Attiya & Jennifer Welch, Distributed Computing: Fundamentals, Simulations, and Advanced Topics, Wiley.
  6. Tom White, Hadoop: The Definitive Guide, O'Reilly.
  7. Martin Kleppmann, Designing Data-Intensive Applications, O'Reilly.

Program Elective-II: Network Security [151609]

  • Unit 1.0: Introduction to Network Security
    • Security fundamentals
    • Security threats and attack vectors
    • Vulnerability assessment
    • Security policies and risk management
    • Overview of cybersecurity frameworks
  • Unit 2.0: Cryptography and Key Management
    • Symmetric key cryptography (DES, AES, RC4)
    • Asymmetric key cryptography (RSA, ECC)
    • Key exchange algorithms (Diffie-Hellman, Public Key Infrastructure PKI)
    • Hash functions (SHA, MD5)
    • Digital signatures and certificates
  • Unit 3.0: Authentication and Access Control
    • User authentication methods (passwords, multi-factor authentication, biometrics)
    • Access control models (DAC, MAC, RBAC)
    • Single Sign-On (SSO)
    • OAuth
    • Kerberos authentication
    • Zero Trust security model
  • Unit 4.0: Network Security Protocols
    • IPSec (AH, ESP)
    • Secure Socket Layer (SSL) and Transport Layer Security (TLS)
    • Virtual Private Networks (VPNs)
    • Wireless security protocols (WEP, WPA, WPA2)
    • Email security (PGP, S/MIME)
  • Unit 5.0: Firewalls, IDS, and Security Architectures
    • Types of firewalls (packet filtering, stateful, proxy-based)
    • Intrusion Detection and Prevention Systems (IDS/IPS)
    • Honeypots and deception technologies
    • Secure network design
    • Zero Trust Architecture
  • Unit 6.0: Emerging Trends and Case Studies
    • Cloud security challenges and solutions
    • IoT security threats and countermeasures
    • AI and ML in cybersecurity
    • Blockchain for security
    • Case studies on recent cyber-attacks and defense strategies

Text/Reference Books:

  1. William Stallings, Network Security Essentials: Applications and Standards, Pearson.
  2. Behrouz A. Forouzan, Cryptography and Network Security, McGraw Hill.
  3. Charlie Kaufman, Radia Perlman, Mike Speciner, Network Security: Private Communication in a Public World, Pearson.
  4. Kaufman, Perlman, and Speciner, Network Security: Private Communication in a Public World, Pearson.
  5. Douglas R. Stinson, Cryptography: Theory and Practice, CRC Press.
  6. Niels Ferguson & Bruce Schneier, Practical Cryptography, Wiley.
  7. Joseph Migga Kizza, Guide to Computer Network Security, Springer.

Program Elective-II: Internet & Intranet Engineering [151610]

  • Unit 1.0: Fundamentals of Internet & Intranet
    • Introduction to Internet and Intranet
    • Evolution of networking
    • Internet architecture and standards
    • Intranet applications in enterprises
    • TCP/IP model
    • IPv4 vs IPv6
    • Domain Name System (DNS)
    • HTTP/HTTPS protocols
  • Unit 2.0: Web Technologies and Communication Protocols
    • Web architecture
    • Client-server model
    • HTTP and Restful APIs
    • Web services (SOAP, REST)
    • FTP
    • SMTP
    • IMAP
    • WebSockets
    • Secure communication protocols (TLS, SSL)
    • Content Delivery Networks (CDN)
  • Unit 3.0: Intranet Design & Enterprise Networking
    • Intranet components
    • Network design principles
    • VLANs and VPNs for intranet
    • Authentication and access control
    • Directory services (LDAP, Active Directory)
    • Single Sign-On (SSO)
    • Proxy servers and load balancing
  • Unit 4.0: Cloud Computing and Virtualization
    • Introduction to cloud computing
    • Intranet integration with cloud services
    • Virtualization technologies (VMware, Hyper-V, KVM)
    • Software-defined networking (SDN)
    • Edge computing for intranet solutions
    • Serverless architecture
  • Unit 5.0: Security and Performance Optimization
    • Security threats in intranet and internet environments
    • Firewalls and IDS/IPS
    • Zero Trust Security model
    • Performance tuning and caching strategies
    • Content optimization (compression, minification, lazy loading)
    • Secure API development
  • Unit 6.0: Emerging Trends and Case Studies
    • IoT and Industrial Intranet
    • Blockchain for secure communication
    • AI-driven networking
    • Digital Twins for enterprise intranets
    • Case studies on large-scale intranet implementations
    • Future trends in Internet and Intranet technologies

Text/Reference Books:

  1. Douglas E. Comer, Internetworking with TCP/IP, Pearson.
  2. Behrouz A. Forouzan, Data Communications and Networking, McGraw Hill.
  3. Andrew S. Tanenbaum, Computer Networks, Pearson.
  4. William Stallings, Data and Computer Communications, Pearson.
  5. Randy J. Boyle, Internet & Intranet Security, Wiley.
  6. Kai Hwang, Geoffrey Fox, Jack Dongarra, Distributed and Cloud Computing, Elsevier.
  7. Paul Deitel, Harvey Deitel, Internet & World Wide Web: How to Program, Pearson.

Program Elective-III: Computer Graphics [151611]

  • Unit 1.0: Introduction and Line Generation
    • Types of computer graphics
    • Graphic Displays- Random scan displays
    • Raster scan displays
    • Frame buffer and video controller
    • RGB color model
    • Direct coding
    • Lookup table; storage tube graphics display
    • Raster scan display
    • 3D viewing devices
    • Plotters
    • Printers
    • Digitizers
    • Light pens etc.
    • Active & Passive graphics devices; Computer graphics software
  • Unit 2.0: Points, Lines and Transformations
    • Points and lines
    • Line drawing algorithms; DDA algorithm
    • Bresenham's line algorithm
    • Circle generating algorithms
    • Mid-point circle generating algorithm
    • And parallel version of these algorithms
    • Ellipse generating algorithm; scan line polygon
    • Fill algorithm
    • Boundary fill algorithm
    • Flood fill algorithm
    • Transformations: Basic transformation
    • Matrix representations and homogenous coordinates
    • Composite transformations
    • Reflections and shearing
  • Unit 3.0: Windowing and Clipping
    • Viewing pipeline
    • Viewing transformations
    • 2-D Clipping algorithms- Line clipping algorithms such as Cohen Sutherland line clipping algorithm
    • Liang Barsky algorithm
    • Line clipping against non-rectangular clip windows; Polygon clipping Sutherland Hodgeman polygon clipping
    • Weiler and Atherton polygon clipping
    • Curve clipping
    • Text clipping
  • Unit 4.0: Three Dimensional
    • 3-D Geometric Primitives
    • 3-D Object representation
    • 3-D Transformation
    • 3-D viewing
    • Projections
    • 3-D Clipping
  • Unit 5.0: Curves and Surfaces
    • Quadric surfaces
    • Spheres
    • Ellipsoid
    • Blobby objects
    • Introductory concepts of Spline
    • Bspline and Bezier curves and surfaces
  • Unit 6.0: Hidden Lines and Surfaces
    • Back Face Detection algorithm
    • Depth buffer method
    • A- buffer method
    • Scan line method
    • Basic illumination models- Ambient light
    • Diffuse reflection
    • Specular reflection and Phong model
    • Combined approach
    • Warn model
    • Intensity Attenuation
    • Color consideration
    • Transparency and Shadows

Text/Reference Books:

  1. Donald Hearn and M Pauline Baker, "Computer Graphics C Version", Pearson Education.
  2. Foley, Vandam, Feiner, Hughes - "Computer Graphics principle", Pearson Education.
  3. Rogers, "Procedural Elements of Computer Graphics", McGraw Hill.
  4. Donald Hearn and M Pauline Baker, "Computer Graphics with OpenGL", Pearson education.

Program Elective-III: Quantum Computing [151612]

  • Unit 1.0: Introduction to Quantum Computing
    • Motivation for studying Quantum Computing
    • Major players in the industry (IBM, Microsoft, Rigetti, D-Wave etc.)
    • Origin of Quantum Computing
    • Overview of major concepts in Quantum Computing
    • Qubits and multi-qubits states
    • Bra-ket notation
    • Bloch Sphere representation
    • Quantum Superposition
    • Quantum Entanglement
  • Unit 2.0: Math Foundation for Quantum Computing
    • Matrix Algebra: basis vectors and orthogonality
    • Inner product and Hilbert spaces
    • Matrices and tensors
    • Unitary operators and projectors
    • Dirac notation
    • Eigen values and Eigen vectors
  • Unit 3.0: Building Blocks for Quantum Program
    • Architecture of a Quantum Computing platform
    • Details of q-bit system of information representation: Block Sphere
    • Multi-qubits States
  • Unit 4.0: Quantum Operations
    • Quantum superposition of qubits (valid and invalid superposition)
    • Quantum Entanglement
    • Useful states from quantum algorithmic perceptive e.g. Bell State
    • Operation on qubits: Measuring and transforming using gates
  • Unit 5.0: Quantum Logic gates and Circuit
    • Pauli
    • Hadamard
    • Phase shift
    • Controlled gates
    • Ising
    • Deutsch
    • Swap etc.
    • Programming model for a Quantum Computing Program: Steps performed on classical computer
    • Steps performed on Quantum Computer
    • Moving data between bits and qubits
  • Unit 6.0: Quantum Algorithms
    • Basic techniques exploited by quantum algorithms
    • Amplitude amplification
    • Quantum Fourier Transform
    • Phase Kick-back
    • Quantum Phase estimation
    • Quantum Walks
    • Major Algorithms: Shor's Algorithm
    • Grover's Algorithm
    • Deutsch's Algorithm
    • Deutsch Jozsa Algorithm
    • OSS Toolkits for implementing Quantum program: IBM quantum experience
    • Microsoft Q. Rigetti PyQuil (QPU/QVM)

Text/Reference Books:

  1. Michael A. Nielsen, "Quantum Computation and Quantum Information", Cambridge University Press.
  2. David McMahon, "Quantum Computing Explained", Wiley.
  3. IBM Experience: [https://quantumexperience.ng](https://quantumexperience.ng),bluemix.net.
  4. Microsoft Quantum Development Kit [https://www.microsoft.com/en-us/quantum/development-kit](https://www.microsoft.com/en-us/quantum/development-kit).
  5. Forest SDK PyQuil: [https://pyquil.readthedocs.io/en/stable/](https://pyquil.readthedocs.io/en/stable/).

Program Elective-III: Block Chain Technology [151613]

  • Unit 1.0: Introduction
    • Overview of Block chain
    • Public Ledgers
    • Bitcoin
    • Smart Contracts
    • Block in a Block chain
    • Transactions
    • Distributed Consensus
    • Public vs Private Block chain
    • Understanding Crypto currency to Block chain
    • Permissioned Model of Block chain
    • Overview of Security aspects of Block chain Basic Crypto Primitives: Cryptographic Hash Function
    • Properties of a hash function
    • Hash pointer and Merkle tree
    • Digital Signature
    • Public Key Cryptography
    • A basic crypto currency
  • Unit 2.0: Understanding Block chain with Crypto currency
    • Bitcoin and Block chain: Creation of coins
    • Payments and double spending
    • Bitcoin Scripts
    • Bitcoin P2P Network
    • Transaction in Bitcoin Network
    • Block Mining
    • Block propagation and block relay
  • Unit 3.0: Working with Consensus in Bitcoin
    • Distributed consensus in open environments
    • Consensus in a Bitcoin network
    • Proof of Work (PoW) - basic introduction
    • Hashcash PoW
    • Bitcoin PoW
    • Attacks on PoW and the monopoly problem
    • Proof of Stake
    • Proof of Burn and Proof of Elapsed Time
    • The life of a Bitcoin Miner
    • Mining Difficulty
    • Mining Pool
  • Unit 4.0: Understanding Block chain for Enterprises
    • Permissioned Block chain: Permissioned model and use cases
    • Design issues for Permissioned block chains
    • Execute contracts
    • State machine replication
    • Overview of Consensus models for permissioned block chain- Distributed consensus in closed environment
    • Paxos
    • RAFT Consensus
    • Byzantine general problem
    • Byzantine fault tolerant system
    • Lamport-Shostak-Pease BFT Algorithm
    • BFT over Asynchronous systems
  • Unit 5.0: Enterprise application of Block chain
    • Cross border payments
    • Know Your Customer (KYC)
    • Food Security
    • Mortgage over Block chain
    • Block chain enabled Trade
    • We Trade - Trade Finance Network
    • Supply Chain Financing
    • Identity on Block chain
  • Unit 6.0: Block chain application development
    • Hyperledger Fabric- Architecture
    • Identities and Policies
    • Membership and Access Control
    • Channels
    • Transaction Validation
    • Writing smart contract using Hyperledger Fabric
    • Writing smart contract using Ethereum
    • Overview of Ripple and Corda

Text/Reference Books:

  1. Melanie Swan, "Block Chain: Blueprint for a New Economy", O'Reilly, 2015.
  2. Josh Thompsons, "Block Chain: The Block Chain for Beginners- Guide to Block chain Technology and Leveraging Block Chain Programming".
  3. Daniel Drescher, "Block Chain Basics", Apress; 1st edition, 2017.
  4. Anshul Kaushik, "Block Chain and Crypto Currencies", Khanna Publishing House, Delhi.
  5. Imran Bashir, "Mastering Block Chain: Distributed Ledger Technology, Decentralization and Smart Contracts Explained", Packt Publishing.
  6. Ritesh Modi, "Solidity Programming Essentials: A Beginner's Guide to Build Smart Contracts for Ethereum and Block Chain", Packt Publishing.
  7. Salman Baset, Luc Desrosiers, Nitin Gaur, Petr Novotny, Anthony O'Dowd, Venkatraman Ramakrishna, "Hands-On Block Chain with Hyperledger: Building Decentralized Applications with Hyperledger Fabric and Composer", Import, 2018

Program Elective-III: Cloud Computing [151614]

  • Unit 1.0: Introduction
    • Distributed Computing and Enabling Technologies
    • Cloud Fundamentals: Cloud Definition
    • Evolution
    • Architecture
    • Applications
    • Deployment models
    • And service models
  • Unit 2.0: Virtualization
    • Issues with virtualization
    • Virtualization technologies and architectures
    • Internals of virtual machine monitors/hypervisors
    • Virtualization of data centers
    • And Issues with Multi-tenancy
  • Unit 3.0: Implementation
    • Study of Cloud computing Systems like Amazon EC2 and S3
    • Google App Engine
    • And Microsoft Azure
    • Build Private/Hybrid Cloud using open source tools
    • SLA management
  • Unit 4.0: Resource Management
    • Cloud resource provisioning plan (advance reservation, on demand plan, spot instances)
    • Various scheduling and load balancing techniques to improve QoS parameters
    • Resource Optimization algorithms
    • Task migration and VM migration technique
  • Unit 5.0: Security
    • Vulnerability Issues and Security Threats
    • Application-level Security
    • Data level Security
    • And Virtual Machine level Security
    • Infrastructure Security
    • And Multi-tenancy Issues
  • Unit 6.0: Advances
    • Green Cloud
    • Mobile Cloud Computing
    • Fog Computing
    • Internet of Things

Text/Reference Books:

  1. Cloud Computing Principles and Paradigms, Rajkumar Buyya, James Broberg, Andrzej Goscinski, Wiley Publishers 2011
  2. Cloud Computing Bible, Barrie Sosinsky, Wiley Publishers 2010
  3. Mastering Cloud computing, Rajkumar Buyya, Christian Vacchiola, S Thamarai Selvi, McGraw Hill 2013
  4. Cloud Security and Privacy: An Enterprise Perspective on Risks and Compliance, Tim Mather, Subra Kumaraswamy, Shahed Latif, O'Reilly 2010
  5. Cloud Computing by Shailendra Singh 2018

Program Elective-III: E-Commerce and ERP [151615]

  • Unit 1.0: Introduction to E- Commerce
    • Evolution of E-commerce
    • Advantage and Disadvantage of E Commerce
    • Roadmap of E-Commerce in India
    • Business Models of E-Commerce: Model Based On Transaction Party: B2B, B2C, C2B, C2C
  • Unit 2.0: E marketing
    • The scope of E-Marketing
    • Identifying Web Presence goals
    • Uniqueness of the web
    • Meeting the need of website visitors
    • Website Design Issues: Factors that make People Return to Your Site
    • Strategies for Website Development
    • Site Adhesion: Content, format and access: maintaining a Website
    • E- Advertising
    • E-Branding
  • Unit 3.0: E-Payment System
    • Digital Payment Requirement
    • Digital Token based E-Payment System
    • Electronic Cash
    • Smart card and Electronics payment system: Credit and Debit Card
    • Virtual Currency
    • Digital wallet
    • Risk of Electronics payment system
  • Unit 4.0: Digital Signature and E Security
    • Digital Signature
    • E Security: Security On the Internet: Network and Website Security Risk: Denial-of-Service attack
    • Viruses
    • Unauthorized access to computer Network
    • Security Standards: Firewall
    • Cryptography
    • Key Management
    • Password Systems
    • Digital certificates
    • Digital signatures
  • Unit 5.0: Enterprise Resource Planning (ERP)
    • Introductory Concepts
    • Advantages & disadvantages of ERP
    • ERP and Related Technologies: - Business Process Reengineering
    • Data Warehousing
    • Data Mining
    • Supply Chain Management
    • ERP Implementation: ERP Implementation Life Cycle Implementation Methodology
    • Hidden Costs
    • Organizing Implementation Contracts with Vendors
    • Consultants and Users
    • Project Management and Monitoring
  • Unit 6.0: ERP Business Modules
    • Introduction to basic Modules of ERP System
    • Business Modules in an ERP Package- Finance Manufacturing - Human Resource Management - Quality Management - Sales and Distribution
    • Plant Maintenance Materials

Text/Reference Books:

  1. Alexis Leon, "ERP Demystified", Tata McGraw Hill.
  2. E-Commerce An Indian Perspective by P.T.Joseph, PHI
  3. K.K. Bajaj, D. Nag "E-Commerce", 2nd Edition, McGraw-Hill Education, New Delhi.
  4. Bhaskar Bharat, "Electronic Commerce-Technology and Application", McGraw-Hill Education, New Delhi.
  5. Mary Sumner, "Enterprise Resource Planning", 2005, PHI Learning India Pvt. Ltd. /Pearson Education, New Delhi.
  6. Chan, "E-Commerce fundamentals and Applications", Wiley India, New Delhi.
  7. Vinod Kumar Garg and N.K. Venkata Krishnan, "Enterprise Resource Planning - concepts and Planning", Prentice Hall, 1998.

Machine Learning Lab [151601P]

List of Experiments:

  • 1. a) Implementation of Python Basic Libraries such as Statistics, Math, Numpy and Scipy b) Implementation of Python Libraries for ML application such as Pandas and Matplotlib.
  • 2. a) Creation and Loading different datasets in Python b) Write a python program to compute Mean, Median, Mode, Variance, Standard Deviation using Datasets
  • 3. a) Write a python program to compute reshaping the data, Filtering the data, merging the data and handling the missing values in datasets
  • 4. a) Write a Python program to implement Simple Linear Regression and plot the graph. b) Implementation of Multiple Linear Regression for House Price Prediction using sklearn
  • 5. Implementation of Logistic Regression for iris using sklearn
  • 6. Implementation of random forest algorithm
  • 7. Implementation of navie bayes classifier algorithm and plot the graph.
  • 8. Implementation of SVM classification and plot the graph.
  • 9. a) Implementation of PCA b) Implementation of LDA.
  • 10. a) Implementation of k-means clustering. b) Implementation of hierarchical clustering

Ad hoc & Network Sensors Lab [151603P]

List of Experiments:

  • Experiment 1: Introduction to Wireless Network Simulation - Overview of NS2/NS3, MATLAB, and OMNET++ for ad hoc and sensor networks. Understanding network topology setup and performance analysis metrics.
  • Experiment 2: Simulation of Ad Hoc Routing Protocols - Implement and analyze AODV, DSR, and DSDV routing protocols. Compare throughput, end-to-end delay, and packet delivery ratio.
  • Experiment 3: MAC Protocol Implementation for Ad Hoc Networks - Implement and analyze contention-based MAC protocols (CSMA, MACA, MACAW). Study the impact of collision avoidance techniques in wireless communication.
  • Experiment 4: Energy-Efficient Routing in Wireless Sensor Networks (WSN) - Implement LEACH (Low-Energy Adaptive Clustering Hierarchy) protocol. Compare energy consumption and network lifetime.
  • Experiment 5: Localization Techniques in WSN - Implement range-based (RSSI, TOA, TDOA) and range-free (DV-Hop, Centroid) localization algorithms. Evaluate accuracy and error rates in node positioning.
  • Experiment 6: Time Synchronization in WSN - Implement RBS (Reference Broadcast Synchronization) and TPSN (Timing-sync Protocol for Sensor Networks). Analyze clock drift and synchronization accuracy.
  • Experiment 7: Data Aggregation in WSN - Implement data aggregation techniques using clustering methods. Compare efficiency in terms of energy saving and data redundancy.
  • Experiment 8: Security Attacks in Ad Hoc and Sensor Networks - Simulate wormhole, blackhole, and Sybil attacks in NS2/NS3. Implement countermeasures for secure routing.
  • Experiment 9: QoS-Based Routing in Ad Hoc Networks - Implement QoS-aware routing using bandwidth and delay constraints. Analyze performance trade-offs between QoS metrics.
  • Experiment 10: Performance Evaluation of Sleep-Wake Scheduling Algorithms - Implement duty-cycle-based sleep-wake scheduling algorithms. Compare energy efficiency and network lifetime improvement.

NPTEL Course-II Lab [151606P]

Details for NPTEL Course-II Lab will be provided by the department.

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