FUNDAMENTALS · EXAM GUIDE

Microsoft Certified: Azure AI Fundamentals (AI-901): exam guide, passing score and how to prepare

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What the Microsoft AI-901 exam covers, what to check before you book, the ideas people mix up, and a simple way to prepare. Last updated .

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Before exam day: what to know about Microsoft AI-901

The real exam is run by the provider. These are the details people look for before they book.

Passing score700

Source: the provider’s official page, checked on 1 November 2026. The provider can change these details at any time.

Your exam-day checklist

  • Confirm the details above on the provider’s page the day you book. Formats and rules change.
  • Match your name and ID. The name on your registration usually has to match your identification. Check the provider’s ID rules.
  • Test your set-up early if you take the exam online: camera, microphone, internet and a clear desk. Providers publish a system test.
  • Know the rules for breaks and materials before you sit. Read the candidate agreement.
  • Rehearse at exam pace. Take your last practice test with a timer and no notes.

What the Microsoft AI-901 exam covers

The Microsoft Certified: Azure AI Fundamentals (AI-901) exam is about AI concepts and Azure AI services. Always check the provider’s official exam guide for the current objectives, fees and format.

Roles this can lead to

  • AI-aware business analyst
  • Junior cloud or AI support specialist
  • Product or project coordinator on AI work
  • Student entering the Azure AI track

Easy to mix up on the Microsoft AI-901 exam

Exam questions often use two ideas that sound alike. Learn the difference once and several questions become easy.

PairThe key differenceHow to choose
Classification or RegressionClassification predicts a category or label, while regression predicts a continuous numeric value.Use classification to decide whether a transaction is fraudulent; use regression to forecast next month's sales figure.
Image classification or Object detectionImage classification assigns a label to the whole image, while object detection finds and locates individual objects, usually with bounding boxes.Choose classification to tag a photo as 'beach'; choose object detection to count and locate the cars in a car park photo.
Prompt engineering or Fine-tuningPrompt engineering shapes the input given to a model at run time, while fine-tuning further trains the model so its weights change.Start with better prompts for quick, cheap improvements; consider fine-tuning when you need consistent specialised behaviour that prompts cannot achieve.
Transparency or AccountabilityTransparency is about people understanding how an AI system works and reaches outputs, while accountability is about people being responsible for the system's impact.Document how a model decides to support transparency; assign owners and review processes to support accountability.

Study notes written by us. Always check the provider’s exam guide for the current objectives.

Practise these in the Microsoft AI-901 tests →

How to prepare in four steps

  1. Read the official exam guideNote the domains and their weights on the provider’s page.
  2. Take Test 1 as a baseline45 questions in 45 minutes, no notes.
  3. Fix the gapsRead every explanation and keep an error log.
  4. Repeat to 80%Two timed tests in a row, then book the exam.

Open the Microsoft AI-901 study plan

TRY ONE QUESTION

See how we explain every option

Each option in our tests has a reason: why the right answer is right and what trap each wrong option sets.

Try the Microsoft AI-901 tests on Udemy →
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TRY ONE QUESTION

A bank finds that its loan approval model approves applicants from one demographic group at a noticeably lower rate than another, even when their finances are similar. Which responsible AI principle is most directly at risk?

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A. Reliability and safetyIncorrect. This principle is about the system performing consistently and safely under expected and unexpected conditions, not about unequal treatment of groups.
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B. Privacy and securityIncorrect. This principle concerns protecting personal data and resisting attacks. The scenario describes unequal outcomes, not data exposure.
✓
C. FairnessCorrect. Fairness means AI systems should treat all people equitably. Different approval rates for similar applicants signal bias that should be assessed and mitigated.
✗
D. TransparencyIncorrect. Transparency is about people understanding how and why a system produces its outputs. It may help diagnose the issue but it is not the principle being violated.

Illustration from the AI topic area. An original question written for this exam’s topics, not an actual exam question.

Frequently asked questions

What is the Microsoft AI-901 exam?

The Microsoft Certified: Azure AI Fundamentals (AI-901) exam is about AI concepts and Azure AI services. We rate it fundamentals level in our guide to help you choose.

What is the passing score for Microsoft AI-901?

700. Source: the provider, checked 1 November 2026. The provider can change this at any time.

Who should take Microsoft AI-901?

It suits people in or moving toward roles such as AI-aware business analyst, Junior cloud or AI support specialist, Product or project coordinator on AI work. A certificate supports an application but does not guarantee a job.

How should I prepare for Microsoft AI-901?

Read the provider's official exam guide, take one timed practice test as a baseline, fix the topics you missed, then repeat until you reach about 80 percent twice in a row. Our Microsoft AI-901 study plan shows the pace.

Not affiliated with, endorsed by or sponsored by any certification vendor or exam body. Certification names, exam codes and product names are trademarks of their respective owners and are used only to identify the exam a practice product prepares for. Our questions are original and are not actual exam questions.