Microsoft / AI development and operations
Operate machine learning and generative AI
Bring Python, machine learning and delivery-pipeline experience. AI-103 is an adjacent role, not a mandatory earlier exam.
Optional foundation
Check your starting knowledge
Use AZ-900 to review the basics. You do not need to take this foundation exam to follow our route. If you already know the material, move on.
AZ-900 — Azure Fundamentals
Core learning · AI-300
Learn the role, one area at a time
Work through the official guide and its learning resources. Use these three study blocks to organize your notes; the official skills outline remains your complete coverage checklist.
- 1.Manage reproducible machine learning workflows
- 2.Deploy and monitor models
- 3.Operationalize and evaluate generative AI solutions
Hands-on consolidation
Put it into practice
Write a release plan for a model with versioned data, evaluation gates, monitoring and rollback. Use a small non-sensitive dataset if implementing it.
Ready to move on when…
You can diagnose a quality regression and reproduce the version that produced it.
Use a dedicated lab and synthetic data, never an employer's production environment. Check licensing and costs before provisioning; budget alerts do not stop spending. Remove resources when finished.
Review & exam planning
Find gaps with our AI-300 test
Try the test, explain each missed answer and return to the corresponding learning topic. Repeat the practical task where needed. A practice score is feedback, not proof of certification readiness.
AI-300 — Machine Learning and Generative AI Operations
Before booking, check the official page for current exam availability, any retirement or beta notice, and the credential's full requirements. This guide does not track completion or award a certificate.
Where these skills can lead
Choose a direction that fits your goal—not every path below.