Graph Algorithms: Solving the Shortest Paths Problem

Finding the quickest route is a fundamental challenge in computer science, powering everything from GPS navigation to network routing. Understanding how to model these problems using graphs is essential for any aspiring developer or computer scientist. This course guides you from the absolute basics of graph theory to implementing robust shortest path algorithms. You will learn how to represent graphs in clean, modern code and choose the right algorithm for any network structure, including those with negative weights. What you'll learn: - Understand foundational graph theory concepts, including directed, undirected, and weighted graphs. - Implement standard graph representations using modern, type-hinted programming structures. - Master Dijkstra's algorithm for finding the quickest paths in non-negative weighted networks. - Apply the Bellman-Ford algorithm to successfully handle graphs with negative edge weights. - Identify and resolve negative cycles that can break standard routing logic. - Analyze the performance and complexity trade-offs of different shortest path strategies. You will start with core definitions and structural representations before moving step-by-step through algorithmic logic and practical, code-based implementations. Designed for beginner programmers and computer science enthusiasts, this text-based course requires only a basic understanding of programming logic. Start reading today to master the core algorithms that power modern navigation and routing systems.