This course introduces core concepts in network science through coding and on-paper exercises. Students will learn to analyze, model, and interpret networks.
- Basic network analysis, paths, and components
- Centralities (degree, betweenness, closeness)
- Random network models (Erdős–Rényi, Watts-Strogatz, Barabási–Albert, extensions)
- Robustness: random failures & targeted attacks
- Modularity & community detection
- Calculations for the friendship paradox
- Trees and spanning trees
- Calculations for extended Barabási–Albert models
- Coding: Implement models, compute measures, visualize results (Python, NetworkX)
- On-paper: Derivations, small graph problems, conceptual tasks