How to Pass AI-901: A 2-Week, Day-by-Day Study Plan

Two weeks is a realistic timeline to pass Azure AI Fundamentals (AI-901) — if you study the right things in the right order. This plan assumes about an hour a day and some familiarity with AI tools at work; if you’re starting from absolute zero, stretch each phase and take three weeks instead. The exam itself: roughly 40–60 questions in 45–60 minutes, 700/1000 to pass, $99, no coding.

One thing before you start: make sure everything you study was written for AI-901, not the retired AI-900 — the 2026 refresh renamed half of Azure’s AI services and made generative AI the heaviest domain. (What changed, exactly.)

Week 1 — fundamentals and the mental map

• Day 1 — Baseline. Skim the official skills outline, then take a free practice set cold. Don’t study first — the point is to find out where you actually stand and which domains feel foreign.
• Days 2–3 — AI workloads + responsible AI. Learn to recognize the workload types (computer vision, NLP, document/knowledge mining, generative AI) from one-line scenarios. Then memorize Microsoft’s six responsible-AI principles cold — fairness, reliability & safety, privacy & security, inclusiveness, transparency, accountability. Scenario-to-principle matching is the single most reliable point-scorer on the exam.
• Days 4–5 — Machine learning vocabulary. Regression predicts a number; classification predicts a category; clustering groups unlabeled data. Features vs labels, training vs validation data, supervised vs unsupervised. These distinctions are tested constantly and they’re pure vocabulary — flashcard material.
• Day 6 — Azure Machine Learning. Know what each capability is for: automated ML (auto-tries algorithms), the designer (no-code pipelines), compute and data assets, the model registry, endpoints (deployment).
• Day 7 — Checkpoint. Another practice set. Compare against Day 1 — your weak domains this time are Week 2’s priorities.

Week 2 — services, generative AI, and exam readiness

• Days 8–9 — The “which service?” drill. Vision vs Document Intelligence vs Face; Language vs Translator vs Speech. The exam relentlessly tests picking the right service for a scenario (“extract tables from invoices” = Document Intelligence). Learn each service by the problem it solves — and learn the current names: Azure AI services (was Cognitive Services), Azure AI Vision (was Computer Vision), Azure AI Language (was Text Analytics/LUIS), Azure AI Document Intelligence (was Form Recognizer).
• Days 10–11 — Generative AI, the heaviest domain (20–25%). Over-invest here: tokens, prompts and completions, embeddings, the Transformer, Azure OpenAI Service (GPT, embeddings, DALL-E), and Azure AI Foundry (was AI Studio) with its model catalog. If you only have time to master one domain deeply, it’s this one.
• Day 12 — Timed full practice. Simulate the real thing: about a minute per question, flag and return, never leave blanks (no penalty for guessing).
• Day 13 — Weak-area cleanup. Drill only the domains you missed on Day 12, and re-run the service rename map one last time — outdated names are the most common self-inflicted wound.
• Day 14 — Light review and book it. Skim the cheat sheet and glossary, sleep well, and book through Pearson VUE. If your practice scores are consistently 80%+, you’re ready.

The three highest-yield things on the whole exam

1. The six responsible-AI principles, matched to one-line scenarios.
2. The “which service?” decision tree with current 2026 names.
3. Generative AI vocabulary — tokens, embeddings, prompts/completions, Azure OpenAI, AI Foundry.

Keep reading: Is Azure AI Fundamentals worth it? An honest review · AI-900 vs AI-901: what changed · Microsoft’s new AI certification path, explained · The free AI-901 study guide

HOW TO // AI is not affiliated with or endorsed by Microsoft. Azure AI Fundamentals, AI-900, and AI-901 are certifications and trademarks of Microsoft Corporation; we reference them descriptively.