Algorithmic Graph Theory and Data Structures

ABOUT THE COURSE:This course offers a comprehensive introduction to the mathematical modeling and algorithmic analysis of graph-based problems. Students will gain a solid foundation in core graph algorithms and the efficient data structures that power them. Through a theoretical concept, the course emphasizes key algorithmic paradigms such as greedy methods, dynamic programming, and augmented data structures in the context of solving real-world problems. A strong focus will be placed on analyzing algorithm performance using time and space complexity, enabling students to assess efficiency and scalability. This course is designed to strengthen problem solving skills and bridge the gap between theory and implementation, the course also serves as a stepping stone for advanced studies and research in algorithmic graph theory, network science, and computational complexity.INTENDED AUDIENCE: Computer SciencePREREQUISITES: Data Structure, Graph Theory and ProbabilityINDUSTRY SUPPORT: Stratign FZE, Dubai(UAE), SAG, DRDO, ISRO, WESEE, NTRO.

Syllabus

Week 1: Introduction to graph theory
Week 2:Graph theoretic problems
Week 3:Sorting and searching algorithms with time complexity
Week 4:Binary Search Tree (BST) Sort, Red Black Tree,
Week 5:Van Emde Boas, Augmented data structure, Computational Geometry
Week 6:Dynamic programming technique
Week 7:Graph Algorithms: Minimum spanning tree problem, Prim's
Week 8:Graph Algorithms: shortest path problem, greedy
Week 9:Graph Algorithms: All pairs shortest path, Floyd Warshall, Johnson Algorithm
Week 10:Graph search: BFS, DFS
Week 11:Disjoint set data structure, network flow
Week 12:Computational Complexity