Students admitted from 2023 onward follow the R23 regulation. Second year kicks off with a mix of core CS theory, math, and the first skill-enhancement electives. Here’s the full course structure for 2-1, followed by unit-wise topic breakdowns for each subject.

Course Structure — II Year I Semester

#CategorySubjectL-T-PCredits
1BS&HDiscrete Mathematics & Graph Theory3-0-03
2BS&HUniversal Human Values2-1-03
3Engineering ScienceDigital Logic & Computer Organization3-0-03
4Professional CoreAdvanced Data Structures & Algorithm Analysis3-0-03
5Professional CoreObject Oriented Programming through Java3-0-03
6Professional CoreAdvanced Data Structures & Algorithm Analysis Lab0-0-31.5
7Professional CoreOOP through Java Lab0-0-31.5
8Skill EnhancementPython Programming0-1-22
9Audit CourseEnvironmental Science2-0-0—

Subjects

Discrete Mathematics & Graph Theory

— builds the logical/mathematical foundation CSE students lean on for algorithms and theory courses later.

  • Unit 1: Propositional & predicate logic, truth tables, inference rules
  • Unit 2: Set theory, relations, functions, lattices
  • Unit 3: Combinatorics — permutations, combinations, recurrence relations & generating functions
  • Unit 4: Graph fundamentals — representations, isomorphism, paths, Eulerian/Hamiltonian graphs
  • Unit 5: Multigraphs, planar graphs, coloring, spanning trees (Prim’s/Kruskal’s), BFS/DFS trees

Universal Human Values

— a mandatory values-and-ethics course common across all JNTUK branches, built around self-exploration rather than exams in the usual sense.

  • Unit 1: Introduction to value education — natural acceptance, happiness and prosperity as human aspirations
  • Unit 2: Harmony within the self — understanding the self as distinct from (and connected to) the body
  • Unit 3: Harmony in the family and society — trust and respect as foundational relationship values
  • Unit 4: Harmony in nature and existence — interconnectedness across the orders of nature
  • Unit 5: Implications for professional ethics — applying the holistic understanding to a working career

Digital Logic & Computer Organization

— how a computer actually works underneath the code.

  • Unit 1: Number systems, binary codes, logic gates, K-map simplification
  • Unit 2: Computer architecture basics, Von Neumann model, bus structures
  • Unit 3: Computer arithmetic (fast adders, multiplication, division), processor organization
  • Unit 4: Memory hierarchy — RAM, ROM, cache, virtual memory
  • Unit 5: I/O organization — interrupts, DMA, standard interfaces

Advanced Data Structures & Algorithm Analysis

— the algorithms course most placement interviews draw from directly.

  • Unit 1: Complexity analysis, AVL trees, B-trees
  • Unit 2: Heaps, graph traversal, divide-and-conquer (quicksort, mergesort, Strassen’s)
  • Unit 3: Greedy & dynamic programming — MST, shortest paths, knapsack, TSP
  • Unit 4: Backtracking & branch-and-bound — 8-queens, subset sum, graph coloring
  • Unit 5: NP-hard/NP-complete theory, Cook’s theorem

Object Oriented Programming through Java

  • Unit 1: Java fundamentals, control statements
  • Unit 2: Classes, objects, constructors, methods
  • Unit 3: Arrays, inheritance, interfaces
  • Unit 4–5: Exception handling, string handling, multithreading, JDBC, JavaFX GUI

Advanced Data Structures & Algorithm Analysis Lab

— the hands-on counterpart to ADSA, where AVL trees, greedy strategies, and backtracking move from the whiteboard into working, debuggable code.

  • Building and operating on AVL trees, B-trees, and min/max heaps, plus BFS/DFS traversals and biconnected-component detection on graphs
  • Benchmarking sorting algorithms (quick sort, merge sort) and implementing minimum-cost spanning trees and single-source shortest-path methods
  • Backtracking and branch-and-bound solutions for the 0/1 knapsack problem, N-Queens, job sequencing, and the travelling salesperson problem

Object Oriented Programming Through Java Lab

— turns the Java theory course into muscle memory, with every OOP concept implemented, run, and broken on purpose so students learn to fix it.

  • Classes, constructors, inheritance, and runtime polymorphism through a sequence of increasingly layered programs
  • Exception handling (built-in and user-defined), multithreading with the Producer-Consumer problem, and custom packages
  • File and stream I/O, JavaFX GUI components, and JDBC connectivity for inserting and deleting database records

Python Programming

— the skill-enhancement course that gets most CSE students writing real Python for the first time, ending with a first taste of data-science tooling.

  • Unit 1: Python basics — identifiers, data types, operators, indentation, and control flow (if/else, loops, exception handling)
  • Unit 2: Functions (arguments, args/*kwargs), string operations, and list creation/indexing/slicing
  • Unit 3: Dictionaries, tuples, and sets — creation, built-in methods, and how the three interrelate
  • Unit 4: File handling (text, binary, CSV, pickle) and object-oriented Python — classes, constructors, encapsulation, inheritance, polymorphism
  • Unit 5: Intro to data science — functional programming, JSON/XML handling, NumPy arrays, and Pandas dataframes

Environmental Science

— a mandatory, ungraded audit course (no credits, but attendance-linked) covering the environmental literacy every engineer is expected to carry into practice.

  • Unit 1: Natural resources and overexploitation — forests, water, minerals, food, and energy resources
  • Unit 2: Ecosystem structure and function, food chains/webs, and biodiversity conservation
  • Unit 3: Pollution — causes, effects, and control across air, water, soil, marine, noise, thermal, and nuclear sources; solid waste and disaster management
  • Unit 4: Sustainable development, environmental ethics, climate change, and India’s environmental legislation
  • Unit 5: Population growth, human health, welfare programmes, and field-based environmental study