Graph Algorithms Learning Roadmap

This repository is designed to help learners understand Graph Algorithms step by step.

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1️⃣ What is an Algorithm? An Algorithm is a step-by-step procedure or set of instructions used to solve a problem.

2️⃣ Recommended Learning Path

Step 1: Graph Basics

• Graph = Nodes (vertices) + Edges
• Examples:
  • Social networks (nodes = people, edges = friendships)
  • Maps (nodes = cities, edges = roads)

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Step 2: Graph Traversal

• BFS (Breadth-First Search)

  • Visits nodes level by level
  • Uses a queue
  • Helps find shortest path in unweighted graphs

• DFS (Depth-First Search)

  • Visits nodes deeply first, then backtracks
  • Uses a stack or recursion
  • Useful for exploring all possible paths

✅ Master BFS & DFS first—they form the foundation for other graph algorithms.

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Step 3: Single Source Shortest Path

• Dijkstra Algorithm

  • Finds shortest path in a weighted graph
  • Cannot handle negative weights

• Bellman-Ford Algorithm

  • Finds shortest path in a weighted graph
  • Works even with negative weights
  • Can also detect negative cycles

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Step 4: Maximum Flow

• Ford-Fulkerson Algorithm