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Advanced Graph Theory Course

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

What will I learn?

This course equips you with vital tools to examine intricate networks assuredly. Learners will calculate structural metrics, centrality measures, and spectral values, utilise community detection techniques, and explore network robustness alongside spreading dynamics. Employing actual datasets and repeatable processes, you gain knowledge of effective algorithms and straightforward interpretations for thorough, evidence-based network examination.

Elevify advantages

Develop skills

  • Master centrality: calculate, assess, and explain core centrality metrics swiftly.
  • Harness spectral methods: apply eigenvalues to evaluate connectivity, mixing rates, and disease outbreaks.
  • Detect communities: implement Louvain, SBM, and spectral clustering using genuine datasets.
  • Model robustness: replicate failures, assaults, and outbreak propagation across networks.
  • Perform scalable analysis: leverage graph tools 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

What our students say

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Very great course. Lots of rich information.
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