Step one: your exam date
This is the only setting on the site, and it drives everything else — the countdown, how many study days you get, what lands on each of them, and when each practice exam is scheduled.
What the exam actually looks like
The facts that shape how you study
| Exam code | AI-900 |
| Certification | Microsoft Certified: Azure AI Fundamentals |
| Questions | Typically 40–60, multiple choice and multiple response |
| Exam time | About 45 minutes, in a 60-minute appointment |
| Score scale | 1–1000 |
| Passing score | 700 |
| Wrong-answer penalty | None — never leave a question blank |
| Prerequisites | None. No coding or data science required. |
What 700 really means
A 700 is not 70% of the questions in a simple sense — Microsoft scales scores and weights harder items more heavily, and it has never published the conversion. But 70% correct is the working assumption everyone uses, and it is what this site is calibrated to.
On a 50-question practice exam that is 35 correct. Miss sixteen and you are out. That sounds tight, and it is: AI-900 is a broad exam with very little partial credit for “sort of knowing” a service.
Almost every question is “which workload is this?” or “which Azure service does this?” Learn to map a business sentence onto exactly one service, and the exam becomes short.
The five skill areas, and what each is worth
These are the official weightings from the Microsoft skills-measured document. The third column is how this site distributes its 50-question practice exams.
| # | Skill area | Official weight | Questions here | Guide |
|---|
Generative AI is the single largest skill area, and it grew the last time Microsoft revised the exam while machine learning shrank. If you are short on time, read the Generative AI guide first and the responsible AI principles second. Together they are close to a third of the exam and they are the two most memorizable areas on it.
Microsoft retired Exam AI-900 on June 30, 2026 and replaced it with AI-901, which leads to the same Azure AI Fundamentals certification. If you already hold the credential from AI-900, it stays valid and does not expire.
This site is built to the AI-900 objectives. Most of what is here still transfers directly — the AI workload vocabulary, the six responsible AI principles, the machine learning fundamentals, the Azure AI service line-up, and the generative AI material all carry over. The main gap is that AI-901 leans harder on building with Microsoft Foundry, agents, and Copilot. Use this site for the fundamentals, then check the current official skills-measured document for whichever exam you are actually booked for.
How the plan is built
There is no fixed number of days. The generator takes the days between today and your exam and fits a real plan into them.
Baseline before you study
Day one is a cold practice exam. Not to feel good — to find the two skill areas that are costing you the most, so the rest of the plan can aim at them.
Three exams, three repairs
Practice exams are spaced across whatever window you have, and each one is followed by a repair day. The repair day is where the score actually moves.
It stretches and it compresses
A long runway gets reinforcement days instead of filler. A short one merges study blocks and drops the optional work. Either way the last day is a taper.
Taking a practice exam measures your score. It does not raise it. The gain comes from the hour afterward, when you work out why each miss happened — a fact you never learned, a fact you know but read past, or a misread question. Sort every miss into one of those three buckets and the fix becomes obvious, because the three have three different fixes.
Your progress
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Everything on this site
Your Study Plan
Day-by-day tasks with checkboxes that save automatically, sized to your exam date. Start here every morning.
AI Workloads & Responsible AI
Naming the workload from a business sentence, plus the six responsible AI principles and the giveaway word for each.
Machine Learning Guide
Regression, classification, clustering, features and labels, the metrics that matter, and what Azure Machine Learning actually does.
Computer Vision Guide
Classification versus detection versus OCR, face capabilities, and choosing between Azure AI Vision, Custom Vision, and Document Intelligence.
NLP Guide
Key phrases, entities, sentiment, summarization, and the split between Azure AI Language, Speech, and Translator.
Generative AI Guide largest area
Tokens, prompts, temperature, grounding, RAG, fine-tuning, and the Azure AI Foundry and Azure OpenAI service line-up.
Topic Drills
Fifteen short timed sets on one skill at a time. Instant scoring and an explanation for every question.
Practice Exams 1–3
Three full-length 50-question exams weighted like the real thing, with scaled scoring and full review mode.
Study Tools
Score estimator, exam timer, 180 flashcards, a searchable Azure AI service reference, and the error log.
Exam day logistics
Whichever way you are testing
- Two forms of ID, one of them government issued with a photo. The names must match your booking exactly.
- Arrive or log in thirty minutes early. Late is the same as absent.
- No notes, no phone, no watch, no second monitor.
- If you are testing online, run the system check on the machine you will actually use, days ahead.
- Online testing also means a clear desk and a clear room. The proctor will make you pan the camera.
- Eat something with protein first. Forty-five minutes is short, but a blood-sugar crash is still real.
Once the clock starts
- Read the last line first. BEST, FIRST, MOST, and NOT each change which answer is correct.
- Watch for “Select two” and “Select three.” Missing one costs the whole question.
- If a question passes about 75 seconds, answer it, mark it for review, and move on.
- Two choices that mean the same thing are usually both wrong.
- Answer every question. There is no penalty, so a blank is strictly worse than a guess.
- Leave five minutes to sweep your marked questions. Do not rewrite answers you were confident about.