Step-by-Step Guide: Breadth-First Search Algorithm in Python

🔍 Explore Breadth-First Search: A Fundamental Graph Traversal Algorithm
In this video, we break down Breadth-First Search (BFS), a core graph traversal algorithm widely used in computer science. Whether you’re preparing for coding interviews or solving real-world problems, this step-by-step guide will help you master BFS.

📌 What You'll Learn:
1️⃣ Algorithm Overview: Understand how BFS explores all nodes at the current depth before moving to the next level, ensuring systematic traversal.

2️⃣ Correctness: Discover why BFS guarantees accurate traversal for both trees and graphs, with clear examples and explanations.

3️⃣ Complexity: Analyze its time complexity (O(V + E)) and space complexity (O(V)), where V is the number of vertices and E is the number of edges.

4️⃣ Efficiency: See where BFS excels, such as finding the shortest path in unweighted graphs, and its limitations in weighted or large graphs.

5️⃣ Scalability: Learn how BFS handles large datasets and graphs, and its trade-offs compared to Depth-First Search (DFS).

6️⃣ Generality: Explore its versatility in traversing both directed and undirected graphs, and its applications across various data structures.

7️⃣ Programming Simplicity: Follow detailed coding examples to implement BFS using queues, with insights into handling edge cases and optimizing performance.

🌟 Bonus: Includes real-world applications like pathfinding, social network analysis, and problem-solving in AI and robotics.

🎯 Perfect For:

Students preparing for coding interviews or exams
Programmers working with graph data structures
Anyone exploring algorithms for shortest path and connectivity problems
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[truonghaiang]

Cái này là tìm đường đi khả thi thôi. Không phải tốt nhất gì đâu nhé. Mình quen tay nên viết nhầm.
This is just finding a feasible path, not the best one. I made a mistake because I'm used to writing it that way.