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Microsoft AI-901 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Identify AI concepts and responsibilities | 40-45% | - Describe principles of responsible AI
|
| Topic 2: Implement AI solutions by using Microsoft Foundry | 55-60% | - Implement AI solutions
|
Microsoft Azure AI Fundamentals Exam: Decide With Evidence
Microsoft recommends these training resources for the Microsoft Azure AI Fundamentals exam:
- Microsoft Learn: AI concepts for developers and technology professionals
- Microsoft Learn: Get started with Microsoft Foundry
Follow the training with steady self-testing — the 132 practice questions from GuideTorrent help you apply theory and fill any gaps the training leaves.
The AI-901 exam is a Microsoft certification exam validating the Microsoft Azure AI Fundamentals syllabus shown above. Candidates in 2026 start with GuideTorrent's 132 practice questions, available as a printable PDF, a Windows Desktop Test Engine, and an Online Test Engine — three versions of the same materials.
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The official Microsoft Azure AI Fundamentals outline defines 2 domains. The leading three are Implement AI solutions by using Microsoft Foundry (55-60%), Identify AI concepts and responsibilities (40-45%). The full list is in the topics section above, and GuideTorrent's 132 practice questions cover each one.
The Microsoft Azure AI Fundamentals exam contains 30-40 to complete within 60 minutes. Timed simulation in the GuideTorrent Desktop Test Engine teaches that rhythm before exam day does.
No required prerequisites; basic understanding of cloud computing and familiarity with Python syntax recommended Since requirements change over time, confirm the latest on the official Microsoft exam page before scheduling.
Three versions of the same study materials: a printable, expert-prepared PDF with free demo download and instant access; a Desktop Test Engine for Windows with customizable simulation and timed modes that works offline; and an Online Test Engine for any browser on Windows, Mac, Android, and iOS with test history and performance review. All 132 practice questions are identical across versions. Every purchase includes 365 days of free updates, a 50% renewal discount afterward, and unlimited computer installations.
The Microsoft Azure AI Fundamentals exam requires 700 to pass, and registration costs $99 USD. A failed attempt means paying the same fee again — a readiness check with the GuideTorrent engines before booking is the cheaper option.
Online proctored or onsite at Pearson VUE test centers Register for the Microsoft Azure AI Fundamentals exam through these official channels:
After booking, GuideTorrent delivers your practice questions within 1 minute — preparation starts the same day.
Microsoft Azure AI Fundamentals Sample Questions:
You are developing an application that will coordinate a travel-booking workflow by gathering user preferences, searching for options, requesting approval, and booking services. The solution will maintain context across the steps.
Which type of Al workload is this an example of?
- A. Agentic Ai
- B. computer vision
- C. generative Al
- D. information extraction
Correct Answer: A 🗳️
Explanation: Only visible for GuideTorrent members. You can sign-up / login (it's free).
You are developing an application that analyzes uploaded video files by using Azure Content Understanding in Foundry Tools.
You need to ensure that the application extracts structured information from the videos.
What should the application call?
- A. the Image Analysis API in Azure Vision in Foundry Tools
- B. Azure OpenAI
- C. Azure Language in Foundry Tools sentiment analysis
- D. the Analyze API in Content Understanding
Correct Answer: D 🗳️
You deploy an Al system to assist with hiring decisions.
Company policy requires that human reviewers oversee Al-generated recommendations and remain responsible for final hiring decisions.
Which Microsoft responsible Al principle is this an example of?
- A. transparency
- B. reliability and safety
- C. fairness
- D. accountability
Correct Answer: D 🗳️
Explanation: Only visible for GuideTorrent members. You can sign-up / login (it's free).
When you design an AI system to assess whether loans should be approved, the factors used to make the decision should be explainable.
This is an example of which Microsoft guiding principle for responsible AI?
- A. transparency
- B. inclusiveness
- C. fairness
- D. privacy and security
Correct Answer: A 🗳️
You are designing a system that will generate insurance quotes automatically.
Match the Microsoft responsible AI principles to the appropriate requirements.
To answer, drag the appropriate principle from the column on the left to its requirement on the right. Each principle may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Correct Answer:
Explanation:
Requirement
Principle
The decision-making process must be recorded so that staff can identify the reasoning behind a particular quote.
Transparency
A customer ' s personal information must be visible only to staff who are involved in the decision-making process.
Privacy and security
The system must be accessible to customers who use screen readers or other assistive technology.
Inclusiveness
Microsoft ' s Responsible AI framework defines six core principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.
The first requirement maps to Transparency because personnel must be able to understand and review how the AI system arrived at an insurance quote. Transparency concerns making AI behavior, capabilities, limitations, and decision processes understandable. Recording the decision-making process provides the traceability required to explain a particular result.
The second requirement maps to Privacy and security. Restricting customer information to authorized staff directly implements least-privilege access and protects confidential personal data from unauthorized disclosure. Microsoft specifically associates this principle with respecting data boundaries and safeguarding information handled by AI systems.
The third requirement maps to Inclusiveness. AI systems should accommodate the full range of people they serve, including individuals who rely on assistive technologies. Support for screen readers and accessibility technologies ensures that users with disabilities are not excluded from interacting with the system. Microsoft explicitly connects inclusive AI design with accessibility considerations for people with disabilities.
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