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Elite Computer Science Mastery
·
Module 5
Graph Algorithms
1
Graph Representations: Adjacency Lists vs. Matrices
Represent graphs using adjacency lists and matrices, and analyze their space-time trade-offs.
2
BFS for Shortest Paths in Unweighted Graphs
Implement Breadth-First Search (BFS) for shortest path in unweighted graphs.
3
DFS: Traversal and Cycle Detection
Implement Depth-First Search (DFS) recursively and iteratively for traversal and cycle detection.
4
Topological Sort for DAGs
Perform a topological sort on a Directed Acyclic Graph (DAG).
5
Dijkstra's Algorithm for Shortest Paths
Implement Dijkstra's algorithm for single-source shortest paths in weighted graphs with non-negative edges.
6
Bellman-Ford for Negative Edge Weights
Implement the Bellman-Ford algorithm to handle graphs with negative edge weights.
7
Kruskal's and Prim's Algorithms for MSTs
Implement Kruskal's and Prim's algorithms to find a Minimum Spanning Tree (MST) in a graph.
Previous module
Hashing, Sets, and Range Queries
Next module
Dynamic Programming and Greedy Algorithms