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The science of relationships, networks, and optimal pathfinding.
Section 1 of 4
"The world isn't hierarchical; it's connected. Master Graph Theory to solve the shortest-path logic of Google Maps and the complex relationship mapping of Facebook."
From raw connections to complex networks.
"Intro to nodes (vertices) and edges. Understanding directed, undirected, weighted, and cyclic graphs."
"Exploring relationships: BFS (Shortest Path) vs DFS (Exhaustive Search). Cycle detection algorithms."
"Industry-standard algorithms: Dijkstra's, Bellman-Ford, and the science of finding the quickest route."
"Topological Sort (Build Orders), Web Crawlers, and Recommendation Engines."
"Optimal for Sparse Networks."
"Optimal for Dense Graphs."
Complexity Pro-Tip
"In graph theory, we use V (Vertices) and E (Edges). Most efficient algorithms aim for O(V + E) time."
Module 5: Trees COMPLETE