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Advanced Graph Theory Course

Advanced Graph Theory Course
from 4 to 360h flexible workload
certificate valid in your country

What will I learn?

This course equips you with essential tools to examine intricate networks effectively. Learners will calculate structural metrics, centrality measures, and spectral properties, utilise community detection techniques, and explore network robustness alongside spreading dynamics. Employing actual datasets and repeatable processes, you gain knowledge of efficient algorithms and precise interpretations for thorough, evidence-based network studies.

Elevify advantages

Develop skills

  • Master centrality: calculate, evaluate, and explain vital centrality metrics swiftly.
  • Harness spectral methods: apply eigenvalues to assess connectivity, mixing rates, and disease outbreaks.
  • Detect communities: implement Louvain, SBM, and spectral clustering using genuine datasets.
  • Model robustness: replicate failures, targeted attacks, and contagion spread across networks.
  • Perform scalable analysis: leverage graph libraries for metrics on vast sparse networks.

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.
Workload: between 4 and 360 hours

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Very great course. Lots of rich information.
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