A comprehensive, beginner-to-advanced guide covering everything you need to master Graph DSA for technical interviews.

---

Follow this path from beginner to advanced:

Step	Topic	What You’ll Learn
1️⃣	Introduction	What are graphs? Terminologies, types, properties
2️⃣	Graph Representations	Adjacency matrix, adjacency list, edge list
3️⃣	Time & Space Complexity	Algorithm complexity, representation trade-offs
4️⃣	Traversals (BFS & DFS)	Breadth-First Search and Depth-First Search
5️⃣	Important Patterns	8 essential patterns with templates
6️⃣	Key Algorithms	Dijkstra, Bellman-Ford, Kruskal, Prim, Floyd-Warshall
7️⃣	Problem-Solving Approach	Decision framework, how to identify graph problems
8️⃣	Code Examples	Full JavaScript implementations
9️⃣	Interview Questions	Categorized Easy/Medium/Hard
🔟	Tips & Mistakes	Best practices, optimization, edge cases
1️⃣1️⃣	Real-World Applications	Graphs in networking, maps, social media, games

---

If You Need This	Go Here
Understand the basics	Introduction →
Pick a BFS/DFS template	Code Examples →
Solve “shortest path” problems	Patterns →
Review for an interview	Interview Questions →
Last-minute tips	Tips & Mistakes →

---

• Trees — A special case of graphs (acyclic, connected)
• Stack & Queue — Fundamental data structures for BFS/DFS
• Recursion & Backtracking — Recursive DFS patterns
• Hashing — Used for visited sets and graph building