Graph Theory and Algorithms delves into the intricate relationships and structures that underpin complex systems, providing participants with the analytical tools necessary to solve real-world problems. The course is structured around project-based learning, where participants will engage in hands-on activities that foster a deep understanding of graph-based models and algorithmic strategies. By applying theoretical concepts to practical scenarios, learners will enhance their problem-solving skills and gain insights into the efficiency of various algorithms.
Participants will explore a range of topics, including the fundamentals of graph structures, traversal algorithms, and optimization techniques. The course culminates in a final project where learners will design and implement a graph-based solution to a specific problem, encouraging the publication of their findings in Cademix Magazine. This approach not only solidifies their learning but also provides an opportunity to contribute to the academic community.
Introduction to Graph Theory: Definitions and Basic Concepts
Types of Graphs: Directed, Undirected, Weighted, and Unweighted
Fundamental Algorithms: Depth-First Search (DFS) and Breadth-First Search (BFS)
Shortest Path Algorithms: Dijkstra’s and Bellman-Ford
Minimum Spanning Trees: Prim’s and Kruskal’s Algorithms
Network Flow: Ford-Fulkerson Method and Applications
Graph Coloring and Its Applications
Advanced Topics: Planar Graphs and Graph Isomorphism
Algorithm Complexity: Big O Notation and Performance Analysis
Final Project: Design and Implementation of a Graph-Based Solution