Breadth-First & Depth-First Search (Data Structures & Algorithms)

Master the logic behind exhaustive graph exploration in this technical deep dive into Breadth-First Search (BFS) and Depth-First Search (DFS). This session is ideal for developers who want to sharpen their problem-solving skills and prepare for coding interviews at top tech companies.

You’ll learn how BFS and DFS traverse graphs and trees in fundamentally different ways. DFS explores deeply along a single branch before backtracking, while BFS expands level by level to systematically explore all nearby nodes first. Understanding when and why to use each approach is a core skill in algorithm design.

We’ll break down the underlying data structures that power these algorithms. You’ll see how Stacks and recursion drive DFS using the "last-in, first-out" (LIFO) principle, and how Queues enable BFS through "first-in, first-out" (FIFO) processing. We’ll also analyze time and space complexity, helping you evaluate which strategy is more efficient based on problem constraints.

This class bridges theory with real-world applications. You’ll discover how BFS and DFS are used in cycle detection, shortest-path discovery, topological sorting, dependency resolution, maze solving, and game AI. Seeing both algorithms side by side will help you design cleaner, more efficient solutions for complex data relationships.

By the end of this live session, you’ll have a solid framework for implementing and choosing between BFS and DFS in practical scenarios. You’ll gain the confidence to identify the right traversal strategy for real engineering problems and apply these techniques effectively in your own code.

The class will take place here - https://www.passionclass.co/en/join-sample-passionclass