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Graph Neural Networks Course

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

What will I learn?

Gain expertise in graph neural networks for predicting service failures and boosting reliability through this practical course. Cover graph basics, observability metrics, and feature engineering for accurate incident forecasting, implement GraphSAGE and GAT with optimised data pipelines and training, and deploy, monitor, and refine GNN models in production for tangible outcomes.

Elevify advantages

Develop skills

  • Design microservice graphs by mapping dependencies, metrics, and failure indicators swiftly.
  • Build GNN models using GraphSAGE and GAT for predicting service health effectively.
  • Engineer graph features by creating node and edge signals to detect outages and SLA risks.
  • Train and evaluate GNNs with strong training loops, baselines, and metrics that account for drift.
  • Deploy GNNs in production environments by serving, monitoring, and scaling low-latency 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... I appreciate everything you do, I've already recommended you to others...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons are 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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