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Graph Neural Networks are one of the most underutilized but powerful deep learning architectures. This course explains graph theory fundamentals, message passing algorithms, and practical GNN implementations across three real domains.

✅ What’s Inside:

  1. Graph Theory Refresher
  2. Why Graphs for AI
  3. Message Passing Framework
  4. Graph Convolutional Networks
  5. Graph Attention Networks
  6. Node Classification Tasks
  7. Link Prediction
  8. Graph-Level Tasks
  9. GraphSAGE for Large Graphs
  10. Knowledge Graph Embeddings
  11. Heterogeneous Graphs
  12. Project: Fraud Detection Network