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

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This course equips you with practical skills to analyse complex networks confidently. You will calculate structural metrics, centrality measures, and spectral properties, perform community detection, and examine network robustness and spreading dynamics. Using real datasets and reproducible methods, you gain expertise in efficient algorithms and clear interpretations for data-driven network analysis.
Elevify advantages
Develop skills
- Master centrality: compute, compare, and interpret key measures quickly.
- Harness spectral tools: apply eigenvalues to assess connectivity, mixing, and outbreaks.
- Detect communities: implement Louvain, SBM, and spectral clustering on actual data.
- Model robustness: simulate failures, attacks, and disease spread across networks.
- Scale analysis: leverage graph libraries for metrics on large sparse graphs.
Suggested summary
Before starting, you can change the chapters and 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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