Azure AI-300 30-, 60-, and 90-day study plan with topic order, review loops, and final-week priorities.
This plan is a compact route for Microsoft Certified: Machine Learning Operations Engineer Associate (AI-300). It assumes you are using TechExamLexicon for concept clarity and the exact IT Mastery page for practice routing.
| Day | Focus | What to do |
|---|---|---|
| Day 1 | Orientation and scope | Read the exam guide overview and official vendor page, then use this study plan to mark the lanes you already know and the lanes that need practice. |
| Day 2 | MLOps infrastructure | Provision workspaces, compute, registries, environments, identity, networking, and IaC for repeatable ML operations. |
| Day 3 | Model lifecycle | Track data, training, evaluation, registration, deployment, monitoring, rollback, and retraining signals. |
| Day 4 | GenAIOps infrastructure | Operationalize prompts, agents, retrieval, model endpoints, evaluations, and content-safety controls. |
| Day 5 | Quality and observability | Measure relevance, groundedness, safety, latency, cost, drift, and incident signals. |
| Day 6 | Optimization | Tune model choice, prompt design, retrieval, batching, caching, endpoint shape, and cost-performance trade-offs. |
| Day 7 | Timed review and scheduling decision | Run a timed practice block, review explanations, update a one-page rule sheet, and verify current vendor facts before scheduling. |