Graph Neural Networks Course
This course teaches graph neural networks for predicting service failures in microservices, covering graph construction, model implementation with GraphSAGE and GAT, feature engineering, training, evaluation, and production deployment for enhanced system reliability.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Master graph neural networks to predict service failures and boost reliability with this focused, hands-on course. You will learn graph basics, 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 workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
As suas aulas são perfeitas. Adquiri o pacote de um ano e, finalmente, tenho a oportunidade de acompanhar diversos temas do meu interesse sem precisar mudar de plataforma... agradeço por tudo o que fazem, já recomendei vocês a outras pessoas...
Giulio CarloAluno de Marketing Digital
Eu gosto de como as lições são direto ao ponto e como eu consigo alterar capítulos e pular conteúdos que não preciso.
Mariana FerresAluna de Fotografia
Gosto do conteúdo e do modo de apresentação e transcrição de vídeos, o que acelera o processo!
Luciana AlvarengaAluna de Design de Unhas
A plataforma é rápida, simples de usar. A diversidade de conteúdo e os vídeos complementares ajudam muito no aprendizado.
Giulio CarloAluno de Engenharia de Prompt
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