Graph Algorithms: Finding and Printing the Shortest Path with BFS

Graphs are foundational data structures used to model everything from social networks to routing algorithms, but finding the most efficient route between two points requires a structured approach. This text-based course guides you through the mechanics of Breadth-First Search (BFS) to solve one of computer science's most common challenges: finding and printing the shortest path in a directed graph. By reading through clear explanations and analyzing step-by-step code implementations, you will transition from understanding basic graph theory to writing robust pathfinding algorithms. You will learn how to represent graphs programmatically, track visited nodes to prevent infinite loops, and reconstruct the exact traversal path. What you'll learn: Understand foundational graph terminology, including vertices, directed edges, and adjacency lists; Implement the Breadth-First Search algorithm using standard queue data structures; Track parent nodes during traversal to reconstruct the exact shortest path; Apply modern programming practices like type hinting and clean variable naming to graph code; Write unit tests to verify your pathfinding function against various graph structures; Analyze the time and space complexity of BFS-based shortest path algorithms. You will start with the core definitions of graphs and queues, move on to writing the traversal logic, and finish by implementing the path reconstruction function. This course is designed for beginner programmers and computer science students looking to strengthen their data structures and algorithms knowledge with no prior graph experience required. Start building your algorithmic foundation today.