Module 1
Google Cloud ML Platform
Google Cloud ML Platform
10h
Leçons vidéo
Exercices
Lab pratique
Vertex AI overview
BigQuery ML
AutoML
AI Platform (legacy) vs Vertex AI
Generative AI avec Vertex AI
Infrastructure GCP (Compute Engine, GKE, Cloud Functions)
Module 2
Data Engineering on GCP
Data Engineering on GCP
12h
Leçons vidéo
Exercices
Lab pratique
BigQuery (analytics, ML)
Cloud Storage et Data Lakes
Dataflow (Apache Beam)
Dataproc (Spark, Hadoop)
Pub/Sub (streaming)
Cloud Composer (Airflow)
Feature Store
Module 3
Model Development
Model Development
15h
Leçons vidéo
Exercices
Lab pratique
Vertex AI Training
Custom training (containers, Python packages)
TensorFlow, PyTorch, scikit-learn
AutoML (Tables, Vision, NLP)
Hyperparameter tuning
Distributed training
TPUs et GPUs
Module 4
GenAI sur Vertex AI
GenAI sur Vertex AI
12h
Leçons vidéo
Exercices
Lab pratique
Vertex AI Generative AI Studio
Foundation models (Gemini, PaLM, Codey)
Prompt engineering
Fine-tuning de foundation models
RAG avec Vertex AI
Vector Search
Grounding with Google Search
Module 5
MLOps et Production
MLOps et Production
15h
Leçons vidéo
Exercices
Lab pratique
Vertex AI Pipelines (Kubeflow Pipelines)
Model Registry et versioning
Endpoints (online prediction)
Batch predictions
Model monitoring (drift detection)
CI/CD avec Cloud Build
Infrastructure as Code (Terraform)
Module 6
Responsible AI
Responsible AI
8h
Leçons vidéo
Exercices
Lab pratique
Fairness et bias detection
Explainability (Vertex Explainable AI)
Privacy-preserving ML
Model cards et documentation
Compliance (GDPR, AI Act)
Module 7
Optimization et Scaling
Optimization et Scaling
8h
Leçons vidéo
Exercices
Lab pratique
Cost optimization
Performance tuning
Distributed training strategies
Model serving optimization
Edge deployment (Coral, TensorFlow Lite)