AI & Machine LearningSemester 3-1 syllabus

Third year opens with core systems and information-retrieval courses — Computer Networks, Operating Systems, and Information Retrieval Systems — while introducing the branch’s first Professional Elective and Open Elective choice points. Two lab courses reinforce networking and retrieval theory, and a Flutter-based UI design course plus a second full-stack development module build front-end and mobile skills. A community service project internship is evaluated this semester as well.

Subjects

Information Retrieval Systems

• Unit 1: Foundations of information storage and retrieval, including domain analysis of IR systems.
• Unit 2: Inverted files and signature files as core indexing structures.
• Unit 3: Advanced text indices, lexical analysis, and PAT trees/arrays.
• Unit 4: Stemming algorithms and thesaurus construction.
• Unit 5: String-searching algorithms, from naive matching through more efficient pattern-matching techniques.

L-T-P: 3-0-0, 3 credits

Computer Networks

• Unit 1: Network types, topologies, and reference models (OSI/TCP-IP).
• Unit 2: The data link layer — framing techniques and flow control.
• Unit 3: Medium access control, including random-access schemes like ALOHA and CSMA.
• Unit 4: Network layer design issues, packet switching, and routing services.
• Unit 5: The transport layer — protocol services, port numbers, and connection management.

L-T-P: 3-0-0, 3 credits

Operating Systems

• Unit 1: OS overview, functions, and services.
• Unit 2: Process concepts, scheduling, threading, and inter-process communication.
• Unit 3: Synchronization tools (critical sections, mutex locks, semaphores) and deadlock handling.
• Unit 4: Memory-management strategies, paging, and virtual memory.
• Unit 5: File systems — interfaces, implementation, and storage internals.

L-T-P: 3-0-0, 3 credits

Professional Elective-I options:

• Software Engineering — covers the evolution of software development practice, project-management complexities, the software design process, coding and testing strategies (including black-box testing), and CASE tools.
• Cloud Computing — covers cloud fundamentals, enabling technologies like virtualization and distributed computing, containerization, cloud economics and interoperability, and emerging serverless/FaaS models.
• Internet of Things — covers IoT technology and architecture, business models for connected devices, web-connectivity design principles, data acquisition and analytics, and cloud-based IoT data platforms.
• Exploratory Data Analysis with Python — covers EDA fundamentals, visual aids like line/bar/scatter charts, data transformation and merging, descriptive statistics, and end-to-end model development and evaluation.
• Automata Theory & Compiler Design — covers regular languages and finite automata, context-free grammars and pushdown automata, lexical analysis and top-down parsing, bottom-up parsing, and intermediate code generation/optimization.

L-T-P: 3-0-0, 3 credits (one option selected)

Open Elective-I is filled either from the cross-department open elective pool (each engineering branch offers a course, commonly foundational subjects like Operating Systems or Database Management Systems, to other departments’ students) or by choosing the in-house alternative, Entrepreneurship Development & Venture Creation.

Information Retrieval Lab

• Representing text documents in a vector-space model and computing inter-document similarity.
• Text preprocessing — stop-word removal and stemming.
• Building an inverted index over a moderately sized document collection.
• Classifying and clustering text documents, and evaluating results with standard metrics.
• Web crawling, topic-specific PageRank computation, matrix decomposition/LSI, and social-media text mining.

L-T-P: 0-0-3, 1.5 credits

Computer Networks Lab

• Setting up LAN devices and implementing data-link framing methods (character/bit stuffing, checksums).
• Implementing Hamming code and CRC-based error detection.
• Building sliding-window protocols (Go-Back-N, selective repeat) and the stop-and-wait protocol.
• Implementing congestion control (leaky bucket) and routing algorithms (Dijkstra’s, distance vector).
• Using Wireshark and Nmap for packet analysis and scanning, plus NS2-based network simulation.

L-T-P: 0-0-3, 1.5 credits

Full Stack Development-2

(Skill Enhancement Course; alternative: SWAYAM Plus Data Engineer/AI Engineer track)

• Express.js fundamentals — routing, HTTP methods, and middleware.
• Sessions, cookies, authentication, and building RESTful APIs in Express.js.
• React.js fundamentals — components, JSX, props, state, and styling.
• Conditional rendering, list rendering, forms, and client-side routing in React.
• React hooks and inter-component data sharing, paired with MongoDB CRUD operations.

L-T-P: 0-1-2, 2 credits

User Interface Design using Flutter

• Installing the Flutter/Dart toolchain and writing introductory Dart programs.
• Exploring core widgets and layout structures (Row, Column, Stack).
• Designing responsive UIs with media queries and breakpoints.
• Implementing navigation, state management, and custom themed widgets.
• Building forms with validation, adding animations, and consuming REST APIs within the UI.

L-T-P: 0-0-2, 1 credit

The Community Service Project Internship completed over the prior summer is formally evaluated this semester for 2 credits.

Semester total: 15-1-10 contact hours, 23 credits. Students may additionally opt into a Minor specialization course (3-0-3, 4.5 credits), a NPTEL/SWAYAM minor course (3 credits), or Honors-pool courses (3 credits each).