• Introduction, DFS and BFS :
• Graph Cycle :
• Topological Sorting :
• Minimum Spanning Tree :
• Back-Tracking :
• Shortest Paths :
• Connectivity :
• Maximum Flow :

STL Implementation of Algorithms :

[1. Kruskal’s Minimum Spanning Tree using STL in C++](https://veil-tanker-0ca.notion.site/1-Kruskal-s-Minimum-Spanning-Tree-using-STL-in-C-be4982a896de403187dee518d01f117b)

[2. Prim’s Algorithm using Priority Queue STL](https://veil-tanker-0ca.notion.site/2-Prim-s-Algorithm-using-Priority-Queue-STL-1b10bb9407ae4a2084e05f6990f8b64a)

[3. Dijkstra’s Shortest Path Algorithm using STL](https://veil-tanker-0ca.notion.site/3-Dijkstra-s-Shortest-Path-Algorithm-using-STL-b8141aee5fc34ef4ac321a16d94e8b53)

[4. Dijkstra’s Shortest Path Algorithm using set in STL](https://veil-tanker-0ca.notion.site/4-Dijkstra-s-Shortest-Path-Algorithm-using-set-in-STL-fbb69ccde1ac408fb4f064ca4e52cbb0)

[5. Graph implementation using STL for competitive programming | Set 2 (Weighted graph)](https://veil-tanker-0ca.notion.site/5-Graph-implementation-using-STL-for-competitive-programming-Set-2-Weighted-graph-472d7aba7af1401bb23a58705c5e12a5)

Hard Problems :

1. Graph Coloring (Introduction and Applications)
2. Greedy Algorithm for Graph Coloring
3. Traveling Salesman Problem (TSP) Implementation
4. Travelling Salesman Problem (Naive and Dynamic Programming)
5. Travelling Salesman Problem (Approximate using MST)
6. Vertex Cover Problem | Set 1 (Introduction and Approximate Algorithm)
7. K Centers Problem | Set 1 (Greedy Approximate Algorithm)
8. Erdos Renyl Model (for generating Random Graphs)
9. Clustering Coefficient in Graph Theory
10. Chinese Postman or Route Inspection | Set 1 (introduction)
11. Hierholzer’s Algorithm for directed graph