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CS201
Semester 2 • Undergraduate
4 Academic Credits
Data Structures and Algorithms
Rigorous asymptotic analysis, balanced search trees (AVL/Red-Black), binary heaps, hash tables, and graph traversals.
Course Learning Outcomes
AVL & Red-Black Trees
Theoretical foundation and algorithmic problem solving with faculty evaluation.
Dijkstra & Prim Algorithms
Theoretical foundation and algorithmic problem solving with faculty evaluation.
Dynamic Programming
Theoretical foundation and algorithmic problem solving with faculty evaluation.
Amortized Analysis
Theoretical foundation and algorithmic problem solving with faculty evaluation.
Curriculum Chapter Syllabus
Chapter 01
Foundational Theory & Invariants
Asymptotic notation, amortized complexity, and invariant proofs.
Big-O / Omega / ThetaMaster TheoremLoop Invariants
Chapter 02
Linear & Hierarchical Data Structures
Dynamic arrays, linked allocation, stacks, queues, and priority heaps.
Fibonacci HeapsArray Doubling AnalysisCircular Queues
Chapter 03
Self-Balancing Binary Search Trees
AVL height balances, single/double rotations, and Red-Black tree coloring rules.
AVL Balance FactorRed-Black InvariantsSplay Trees
Chapter 04
Graph Traversals & Optimal Pathing
Breadth/depth traversals, topological sorting, shortest paths, and minimum spanning trees.
Dijkstra AlgorithmBellman-Ford Dynamic ProgrammingKruskal & Prim