Machine Learning Operations Engineer Associate (AI-300)

Learn to operationalize machine learning and generative AI solutions on Azure and prepare for exam AI-300. The course follows the official skills measured.

What you'll learn

• Build MLOps infrastructure with IaC
• Train, register, deploy and monitor models
• Build GenAIOps infrastructure in Foundry
• Evaluate and observe generative AI apps and agents
• Optimize RAG and fine-tune models

Course outline

1. Design and Implement an MLOps Infrastructure (15–20%)
   • Machine Learning workspace resources
   • Workspace assets
   • Infrastructure as code for ML
2. Model Life Cycle and Operations (25–30%)
   • Orchestrate model training
   • Model registration and versioning
   • Deploy models to production
   • Monitor and maintain models
3. Design and Implement a GenAIOps Infrastructure (20–25%)
   • Foundry environments
   • Deploy and manage foundation models
   • Prompt versioning with source control
4. Generative AI Quality Assurance and Observability (10–15%)
   • Evaluation and validation
   • Observability for apps and agents
5. Optimize Generative AI Systems (10–15%)
   • Optimize RAG
   • Fine-tuning and customization