Advanced Graph Theory Course
Master advanced graph theory through centrality measures, spectral methods, community detection, an spreading processes. Learn to model real-world networks, run robust simulations, an transform complex structures into clear, actionable mathematical insights fi better decision-making.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This course equips you with practical tools fi analyze complex networks confidently. You'll compute structural metrics, centrality measures, an spectral quantities, apply community detection, an study robustness an spreading processes. Using real-world datasets an reproducible workflows, yuh learn efficient algorithms an clear interpretations fi rigorous, data-driven network analysis.
Elevify advantages
Develop skills
- Master centrality: compute, compare, an interpret key measures swiftly.
- Harness spectral tools: use eigenvalues to diagnose connectivity, mixing, an epidemics.
- Detect communities: apply Louvain, SBM, an spectral clustering on real data.
- Model robustness: simulate failures, attacks, an epidemic spread on networks.
- Scale analysis: leverage graph libraries fi 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 are saying
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