- Focused specifically on graphs and networked data, not tabular or image data.
- Covers embeddings, GNN architectures, and knowledge graph construction.
- Includes real-world projects like social network link prediction and biological node classification.
- Unlike general ML courses, emphasizes code-first, graph-centric workflows.
- Provides hands-on experience with graph analytics pipelines from scratch.
