| # | Category | Subject | L-T-P | Credits |
|---|---|---|---|---|
| 1 | BS&H | Discrete Mathematics & Graph Theory | 3-0-0 | 3 |
| 2 | BS&H | Universal Human Values – Understanding Harmony and Ethical Human Conduct | 2-1-0 | 3 |
| 3 | Engineering Science | Digital Logic & Computer Organization | 3-0-0 | 3 |
| 4 | Professional Core | Advanced Data Structures & Algorithms | 3-0-0 | 3 |
| 5 | Professional Core | Object Oriented Programming Through Java | 3-0-0 | 3 |
| 6 | Professional Core | Advanced Data Structures Lab | 0-0-3 | 1.5 |
| 7 | Professional Core | Object Oriented Programming Through Java Lab | 0-0-3 | 1.5 |
| 8 | Skill Enhancement Course | Python Programming | 0-1-2 | 2 |
| 9 | Audit Course | Environmental Science | 2-0-0 | – |
| Total | 16-2-8 | 20 |
Discrete Mathematics & Graph Theory
builds the logical and combinatorial toolkit (propositional logic, set theory, counting, recurrence relations, and graph theory) that underpins algorithm analysis, database theory, and reasoning about computation throughout the IT curriculum.
- Unit 1: Mathematical logic — propositional calculus, well-formed formulas, truth tables, normal forms, and predicate calculus with quantifiers
- Unit 2: Set theory — set operations, relations, partial ordering, Hasse diagrams, functions, and lattices
- Unit 3: Combinatorics — counting principles, permutations and combinations, and generating functions for recurrence relations
- Unit 4: Graph theory basics — graph representations, isomorphism, paths, circuits, and Eulerian/Hamiltonian graphs
- Unit 5: Multigraphs — bipartite and planar graphs, graph colouring, spanning trees, and BFS/DFS spanning tree algorithms
Universal Human Values – Understanding Harmony and Ethical Human Conduct
a values-education course that helps students connect self-awareness, relationships, and professional ethics into a coherent, practice-based way of living and working.
- Unit 1: Introduction to value education — self-exploration, natural acceptance, and the basic aspirations of happiness and prosperity
- Unit 2: Harmony in the human being — understanding the self as distinct from yet connected to the body
- Unit 3: Harmony in family and society — trust and respect as foundational relational values
- Unit 4: Harmony in nature and existence — interconnectedness across the four orders of nature
- Unit 5: Implications for professional ethics — translating holistic understanding into ethical human and professional conduct
Digital Logic & Computer Organization
covers how data is represented and processed at the hardware level, from logic gates up through processor and memory organization, giving IT students the hardware foundation that every higher software layer sits on.
- Unit 1: Data representation and digital logic circuits — number systems, binary codes, logic gates, K-map minimization, decoders, and multiplexers
- Unit 2: Sequential circuits and computer basics — flip-flops, counters, registers, computer types, and Von Neumann architecture
- Unit 3: Computer arithmetic and processor organization — signed number addition/multiplication, fast adders, and instruction execution control
- Unit 4: Memory organization — RAM/ROM, cache memory, virtual memory, and secondary storage
- Unit 5: I/O organization — interrupts, DMA, buses, interface circuits, and standard I/O interfaces
Advanced Data Structures & Algorithms
extends basic data structures into balanced trees, graphs, and heaps, and pairs them with the classical algorithm-design paradigms (divide-and-conquer, greedy, dynamic programming, backtracking) needed to reason about efficiency and complexity.
- Unit 1: Algorithm analysis and tree structures — asymptotic notation, AVL trees, and B-trees
- Unit 2: Heaps, graphs, and divide-and-conquer — priority queues, graph traversal, quicksort, mergesort, and Strassen’s matrix multiplication
- Unit 3: Greedy and dynamic programming — job sequencing, knapsack variants, shortest paths, and the travelling salesperson problem
- Unit 4: Backtracking and branch-and-bound — N-queens, subset-sum, graph colouring, and 0/1 knapsack
- Unit 5: NP-completeness — Cook’s theorem, NP-hard graph problems, and NP-hard scheduling problems
Object Oriented Programming Through Java
teaches core object-oriented design through Java syntax, class design, inheritance, and exception handling, then extends into threads, file I/O, JDBC, and JavaFX so students can build complete desktop applications.
- Unit 1: Java fundamentals — program structure, data types, operators, and control statements
- Unit 2: Classes and methods — constructors, access control, method overloading, and passing arguments
- Unit 3: Arrays and inheritance — array operations, inheritance types, abstract classes, and interfaces
- Unit 4: Packages and exceptions — package structure, exception hierarchy, and Java I/O streams
- Unit 5: Strings, threads, and connectivity — string handling, multithreading, JDBC database access, and JavaFX GUI basics
Advanced Data Structures Lab
hands-on companion to the algorithms course, where students implement and benchmark the trees, graph algorithms, and optimization strategies covered in lecture.
- Constructing and manipulating AVL trees, B-trees, and min/max heaps with insert/delete operations
- Implementing graph traversals, spanning tree algorithms, and shortest-path methods
- Applying backtracking and branch-and-bound to N-Queens, 0/1 knapsack, and travelling salesperson problems
Object Oriented Programming Through Java Lab
practical Java programming exercises that reinforce class design, inheritance, exception handling, threading, and database connectivity from the lecture course.
- Implementing classes, constructors, method overloading, and inheritance hierarchies
- Building exception handlers, multithreaded programs, and package-based applications
- Connecting to databases via JDBC and building simple JavaFX interfaces
Python Programming
a skill-enhancement course that gets students comfortable writing practical Python, from core syntax through data structures, file handling, object orientation, and an introduction to the data-science stack (NumPy, Pandas).
- Unit 1: Python basics — identifiers, control flow statements, and the Jupyter/Anaconda environment
- Unit 2: Functions and collections — function definitions, argument handling, strings, and lists
- Unit 3: Dictionaries, tuples, and sets — creation, built-in methods, and conversions between them
- Unit 4: Files and OOP — file I/O, pickling, CSV handling, and Python classes/objects
- Unit 5: Intro to data science — NumPy arrays, Pandas data frames, and JSON/XML handling
Environmental Science
a mandatory awareness course on natural resources, ecosystems, pollution, and sustainability, framed around the responsibility engineers carry when their work touches the environment.
- Unit 1: Multidisciplinary nature of environmental studies and renewable/non-renewable natural resources
- Unit 2: Ecosystems and biodiversity — structure, function, and conservation of biodiversity
- Unit 3: Environmental pollution — causes, effects, and control of air, water, soil, and other pollution types
- Unit 4: Social issues — sustainable development, water conservation, climate change, and environmental legislation
- Unit 5: Human population and environment — population growth, health, and the role of IT in environmental monitoring