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Graph Neural Networks Course

Graph Neural Networks Course
4 to 360 hours of flexible workload
certificate valid in your country

What Will I Learn?

Master graph neural networks to predict service failures and improve reliability with this focused, hands-on course. You will learn graph fundamentals, observability metrics, and feature engineering for real incident prediction, then implement GraphSAGE and GAT using efficient data pipelines and training loops. Finally, you’ll deploy, monitor, and update GNN models in production with confidence and clear, measurable results.

Elevify Advantages

Develop Skills

  • Design microservice graphs: map dependencies, metrics, and failure signals fast.
  • Build GNN models: implement GraphSAGE/GAT for service health prediction.
  • Engineer graph features: craft node and edge signals for outages and SLA risk.
  • Train and evaluate GNNs: run robust loops, baselines, and drift-aware metrics.
  • Deploy GNNs in production: serve, monitor, and scale low-latency graph models.

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.
Workload: between 4 and 360 hours

What our students say

Your classes are perfect. I got the one-year package and finally have the chance to follow several topics I'm interested in without having to switch platforms... thank you for everything you do, I've already recommended you to others...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons get straight to the point and how I can switch chapters and skip content I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the supplementary videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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