Advanced Graph Theory Course
Dive deep into advanced graph theory, mastering centrality measures, spectral methods, community detection, and spreading processes. Learn to model real-world networks, conduct robust simulations, and transform intricate structures into actionable mathematical insights for practical applications.

from 4 to 360h flexible workload
certificate valid in your country
What will I learn?
This course equips you with practical tools to analyse complex networks confidently. You'll calculate structural metrics, centrality measures, and spectral quantities, implement community detection, and explore robustness and spreading processes. Using real-world datasets and reproducible workflows, master efficient algorithms and clear interpretations for rigorous, data-driven network analysis.
Elevify advantages
Develop skills
- Master centrality: compute, compare, and interpret key measures swiftly.
- Harness spectral tools: apply eigenvalues to assess connectivity, mixing, and epidemics.
- Detect communities: implement Louvain, SBM, and spectral clustering on real data.
- Model robustness: simulate failures, attacks, and epidemic spread in networks.
- Scale analysis: leverage graph libraries for metrics on large sparse graphs.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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