Cyber SecuritySemester 2-1 syllabus

This semester lays the mathematical and programming groundwork for the Cyber Security branch, pairing discrete mathematics and digital logic with object-oriented Java and modern data-structure design. A humanities course on human values and an audit course on environmental science round out the load alongside an introductory Python skill-enhancement course.

Subjects

Discrete Mathematics & Graph Theory

• Unit 1: Mathematical logic — propositional statements, truth tables, logical equivalence, and predicate logic with quantifiers.
• Unit 2: Set theory — set operations, relation properties, equivalence and partial orders, and function types including bijections and recursive functions.
• Unit 3: Combinatorics and recurrence relations — counting principles, permutations/combinations, generating functions, and methods for solving recurrences.
• Unit 4: Graph theory fundamentals — graph representation, isomorphism, paths, and Eulerian/Hamiltonian graphs.
• Unit 5: Multigraphs — planarity, graph coloring, spanning trees, and BFS/DFS-based spanning tree construction.
• Credit structure: L-T-P-C = 3-0-0-3.

Universal Human Values — Understanding Harmony and Ethical Human Conduct

• Unit 1: Introduction to value education and the idea of holistic human development.
• Unit 2: Harmony within the individual — distinguishing the needs of self and body.
• Unit 3: Harmony in family and society, built around trust and mutual respect.
• Unit 4: Harmony with nature and existence, framed as interconnected orders of reality.
• Unit 5: Implications for professional ethics and value-based living in a career context.
• Credit structure: L-T-P-C = 2-1-0-3.

Digital Logic & Computer Organization

• Unit 1: Number systems, binary codes, and basic combinational logic circuits including decoders and multiplexers.
• Unit 2: Sequential circuits (flip-flops, counters, registers) and the basic structure of a computer system.
• Unit 3: Computer arithmetic for addition, multiplication, and division, plus processor organization and control.
• Unit 4: Memory hierarchy — RAM, ROM, cache, and virtual memory concepts.
• Unit 5: Input/output organization, interrupts, and direct memory access.
• Credit structure: L-T-P-C = 3-0-0-3.

Advanced Data Structures & Algorithm Analysis

• Unit 1: Complexity analysis fundamentals alongside AVL and B-tree construction and maintenance.
• Unit 2: Heaps, graph traversal and connectivity, and divide-and-conquer algorithms like quicksort and mergesort.
• Unit 3: Greedy algorithms and dynamic programming, covering shortest paths and optimal search trees.
• Unit 4: Backtracking and branch-and-bound strategies applied to classic combinatorial problems.
• Unit 5: NP-hard and NP-complete problem classification and related scheduling problems.
• Credit structure: L-T-P-C = 3-0-0-3.

Object Oriented Programming Through Java

• Unit 1: Java program structure, data types, operators, and control statements.
• Unit 2: Classes, objects, constructors, and method design.
• Unit 3: Arrays and the inheritance/interface model in Java.
• Unit 4: Packages, the core Java library, exception handling, and file I/O.
• Unit 5: String handling, multithreading, JDBC database connectivity, and JavaFX GUI basics.
• Credit structure: L-T-P-C = 3-0-0-3.

Advanced Data Structures and Algorithm Analysis Lab

• Focus: hands-on construction and manipulation of AVL trees, B-trees, and heaps, plus implementation of the algorithm design strategies covered in the theory course.
• Representative exercises: building and traversing trees from file input, comparing sorting algorithm runtimes, and solving shortest-path, knapsack, and N-Queens problems programmatically.
• Credit structure: L-T-P-C = 0-0-3-1.5.

Object Oriented Programming Through Java Lab

• Focus: applying Java OOP concepts practically — classes, inheritance, exception handling, threads, and GUI basics.
• Representative exercises: implementing overloaded constructors and methods, multilevel inheritance, custom exceptions, multithreaded programs, and small JavaFX interfaces.
• Credit structure: L-T-P-C = 0-0-3-1.5.

Python Programming

(Skill Enhancement Course)

• Unit 1: Language basics — syntax, data types, control flow, and exception handling.
• Unit 2: Functions, string handling, and list operations.
• Unit 3: Dictionaries, tuples, and sets, with attention to how these structures relate to each other.
• Unit 4: File handling and object-oriented programming in Python.
• Unit 5: An introduction to data science tooling, including NumPy and Pandas.
• Credit structure: L-T-P-C = 0-1-2-2.

Environmental Science

(Audit Course)

• Unit 1: The multidisciplinary scope of environmental studies and classification of natural resources.
• Unit 2: Ecosystem structure and function, and the fundamentals of biodiversity conservation.
• Unit 3: Causes, effects, and control measures for major categories of pollution and solid waste.
• Unit 4: Social dimensions of sustainability, including water conservation and environmental legislation.
• Unit 5: Population growth and its relationship to human health, welfare programs, and community fieldwork.
• Credit structure: L-T-P-C = 2-0-0-0 (audit, non-credit bearing).

Semester load: 16-2-8 contact hours, 20 credits total, plus a mandatory 8-week community service project internship during the following summer.