Shortest Paths in Unweighted Graphs with BFS

Finding the most efficient route through a network is a fundamental challenge in computer science, web crawling, and social network analysis. In this text-only course, you will learn how to use the Breadth-First Search (BFS) algorithm to solve the shortest path problem in unweighted directed graphs. You will transition from understanding basic graph definitions to writing clean, optimized pathfinding code and analyzing its performance. What you'll learn: Understand foundational graph theory concepts, including directed graphs, adjacency lists, and vertex degrees; Implement the Breadth-First Search algorithm from scratch using queue-based structures; Trace how BFS constructs a shortest-path tree to find the minimum number of edges between nodes; Analyze the time and space complexity of BFS using Big O notation to ensure your code runs efficiently; Handle common edge cases such as disconnected components, self-loops, and cyclic paths; Apply modern coding practices, including type hints and structured representations, to your graph algorithms. The course begins with core terminology and graph representation methods before moving step-by-step through the mechanics of BFS traversal. You will read detailed code walk-throughs and practice with written exercises designed to solidify your conceptual understanding. This course is designed for beginner programmers, computer science students, and aspiring software engineers who want to build a strong foundation in graph algorithms. No prior graph theory experience is required, though basic familiarity with programming logic is helpful. Start reading today to master one of the most essential algorithms in computer science.