India
Module 1: MLOps Fundamentals
Introduction to ML lifecycle, DevOps for ML, Azure ML workspace setup
Module 2: Infrastructure Design
Compute targets, environment management, Infrastructure as Code with Bicep
Module 3: Model Training and Registration
Automated training pipelines, model versioning, experiment tracking
Module 4: CI/CD for ML
GitHub Actions, Azure DevOps pipelines, automated testing for models
Module 5: GenAIOps
Microsoft Foundry, deploying LLMs, RAG pipeline optimization
Module 6: Monitoring and Governance
Model monitoring, data drift detection, responsible AI practices
