Скачать или смотреть 🎓 Course Schedule II | Graph | Leetcode 210 Solution 📘 | Topological Sorting

Welcome to the world of course scheduling! 📚 In this video, we'll tackle the "Course Schedule II" problem from LeetCode, exploring how to efficiently organize your course load to ensure you meet all prerequisites. 🚀

Problem Overview:
You're given a total of numCourses courses labeled from 0 to numCourses - 1, along with an array prerequisites indicating prerequisite relationships. Each pair [ai, bi] indicates that you must take course bi before course ai. Your task is to return the ordering of courses you should take to finish all courses. If multiple valid answers exist, return any of them. If it's impossible to finish all courses due to cyclic dependencies, return an empty array.

Approach:
We'll solve this problem using a combination of topological sorting and cycle detection techniques.

We construct an adjacency list representing the course dependencies.
We perform a DFS traversal to detect cycles in the graph, ensuring there are no cyclic dependencies.
If no cycles are found, we perform a topological sort to determine the course order.
Finally, we return the ordered courses as the solution.
Complexity Analysis:

Time Complexity: O(V + E), where V is the number of courses and E is the number of dependencies (edges).
Space Complexity: O(V + E), for storing the adjacency list and visited arrays.
By understanding this approach, you'll gain valuable insights into efficiently organizing your course schedule and handling dependency graphs effectively.

So, are you ready to dive into the fascinating world of course scheduling algorithms? Let's get started and master the art of course planning! 🎓

Course Schedule II, Topological Sort, Cycle Detection, Graph Theory, Leetcode, Coding Interviews, #TopologicalSort #CycleDetection #GraphTheory #LeetCode #CodingInterviews 📝