EC202: Graph Theory for Humans & Machines

Understanding Networks Everywhere

Friend graphs, knowledge graphs, call graphs—it's all nodes & edges

What You Learn

• Graph vocab: nodes, edges, weights, directions
• Traversal patterns (BFS/DFS) as exploration mindsets
• DAGs vs cycles, topological ordering, dependencies
• Shortest paths, centrality, flow
• Knowledge graphs + graph databases

Outcomes

• Model any system as a graph quickly
• Choose traversal/analysis techniques on instinct
• Design graph-backed features for apps, data, AI

Modules

1. Graphs in Nature & Software
2. Traversal Algorithms & Mental Modes
3. Paths, Connectivity & Optimization
4. Graph Storage (adjacency, property/graph DBs)
5. Graphs in AI & Hackathons

Connections

• Builds on EC201
• Supports EC302, EC402, hackathon idea banks

Difficulty: ⭐⭐⭐☆☆ | Time: 10 hours | Prereq: EC201