Microsoft AI-901 exam dumps : Microsoft Azure AI Fundamentals

Exam Code: AI-901
Exam Name: Microsoft Azure AI Fundamentals
Updated: Oct 15, 2026 Q & A: 132 Questions and Answers

PDF Version Demo

PDF Price: $59.99

PC Test Engine

Software Price: $59.99

Microsoft AI-901 Value Pack (Frequently Bought Together)

If you purchase Microsoft AI-901 Value Pack, you will also own the free online test engine.
PDF Version + PC Test Engine + Online Test Engine
Value Pack Total: $119.98 $79.99
Save 49%

About Microsoft AI-901 Exam

Do you still love the feel of a printed book? The PDF version of the Microsoft Azure AI Fundamentals materials at PracticeTorrent was compiled for you: download it, print it, and mark the important knowledge points right on the paper — a time-tested way to work through the difficult parts of the AI-901 exam content.

Microsoft AI-901 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Describe features of generative AI workloads on Azure (20-25%)	20-25%	- Identify features of generative AI solutions 1. Identify features of generative AI models 2. Identify common scenarios for generative AI 3. Identify responsible AI considerations for generative AI - Identify generative AI services and capabilities in Microsoft Azure 1. Describe features and capabilities of Azure AI Foundry model catalog 2. Describe features and capabilities of Azure OpenAI service 3. Describe features and capabilities of Azure AI Foundry
Topic 2: Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)	15-20%	- Identify Azure tools and services for NLP workloads 1. Describe capabilities of the Azure AI Language service 2. Describe capabilities of the Azure AI Speech service - Identify features of common NLP workload scenarios 1. Identify features and uses for speech recognition and synthesis 2. Identify features and uses for key phrase extraction 3. Identify features and uses for translation 4. Identify features and uses for language modeling 5. Identify features and uses for entity recognition 6. Identify features and uses for sentiment analysis
Topic 3: Describe fundamental principles of machine learning on Azure (15-20%)	15-20%	- Identify common machine learning techniques 1. Identify clustering machine learning scenarios 2. Identify features of deep learning techniques 3. Identify classification machine learning scenarios 4. Identify regression machine learning scenarios - Describe core machine learning concepts 1. Describe how training and validation datasets are used in machine learning 2. Identify features and labels for training data in machine learning - Describe Azure Machine Learning capabilities 1. Describe model management and deployment capabilities in Azure Machine Learning 2. Describe data and compute services for data science and machine learning 3. Describe capabilities of automated machine learning
Topic 4: Describe Artificial Intelligence workloads and considerations (15-20%)	15-20%	- Identify features of common AI workloads 1. Identify features of document intelligence workloads 2. Identify features of computer vision workloads 3. Identify features of Natural Language Processing (NLP) workloads 4. Identify features of knowledge mining workloads 5. Identify features of content moderation and moderation workloads 6. Identify features of generative AI workloads - Identify guiding principles for responsible AI 1. Describe considerations for reliability and safety in an AI solution 2. Describe considerations for inclusiveness in an AI solution 3. Describe considerations for privacy and security in an AI solution 4. Describe considerations for fairness in an AI solution 5. Describe considerations for transparency in an AI solution 6. Describe considerations for accountability in an AI solution
Topic 5: Describe features of computer vision workloads on Azure (15-20%)	15-20%	- Identify common types of computer vision solution 1. Identify features of image analysis solutions 2. Identify features of object detection solutions 3. Identify features of optical character recognition (OCR) solutions 4. Identify features of image classification solutions 5. Identify features of face detection and identification solutions 6. Identify features of semantic segmentation solutions - Identify Azure tools and services for computer vision tasks 1. Describe capabilities of the Azure AI Face detection service 2. Describe capabilities of the Azure AI Vision service

The Microsoft Azure AI Fundamentals Exam: Your Questions, Answered

What is the passing score for the AI-901 exam, and what is the fee?

You need 700 / 1000 to pass the AI-901 exam, and registration costs USD 99. Since each attempt carries the fee, candidates who practice thoroughly first — on paper, on screen, under time pressure — put their money behind preparation rather than retakes.

What does the Microsoft Azure AI Fundamentals certification represent?

The AI-901 exam is the official test for the Microsoft Azure AI Fundamentals certification from Microsoft. For graduates and job seekers facing drastic competition, it does something a resume line cannot: it verifies your skills against a recognized standard, so when you enter an interview process, the credential helps you stand out on evidence rather than adjectives.

Which topics does the AI-901 exam focus on?

The official outline divides the AI-901 exam into weighted domains, including:

Describe fundamental principles of machine learning on Azure (15-20%) (15-20%)
Describe features of computer vision workloads on Azure (15-20%) (15-20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%) (15-20%)

Print the Microsoft Azure AI Fundamentals PDF from PracticeTorrent and mark these domains' key points directly on paper — annotating the difficult parts is a proven way to make them stick.

What prerequisites does the AI-901 exam have?

No prerequisites. This exam is intended for both technical and non-technical backgrounds. Data science and software engineering experience are not required. Awareness of basic cloud concepts and client-server applications is beneficial.

Why is the PDF version ideal if I prefer printed books?

Because it was compiled with readers like you in mind. Download the AI-901 exam PDF from PracticeTorrent, print it, and the Microsoft Azure AI Fundamentals content becomes a physical workbook: make notes in the margins, mark the important knowledge points on paper, and carry the pages anywhere — library, dormitory, wherever you study. Reviewing with your own annotations is efficient, and the tactile process keeps you motivated to continue. Many candidates find that once they start, learning this way becomes a genuinely happy process.

How many questions does the AI-901 exam have, and how much time is allowed?

The AI-901 exam includes 40-60 questions to be completed within 45-60 minutes. Time is money during preparation too — focused practice on exam-aligned questions is the shortest route to feeling ready.

Are the Microsoft Azure AI Fundamentals materials safe to download and install?

Yes — safety is engineered in, not just claimed. The AI-901 exam package from PracticeTorrent is verified virus-free, and the exam engine carries a self-protect function, so installing it on your device never puts your important files at risk. Delivery is automatic by email about a minute after payment; if the message is missing, check your spam folder, and contact support if nothing arrives within 2 hours.

Microsoft Azure AI Fundamentals Sample Questions:

Question #1

In the Microsoft Foundry portal, you create an agent named Agent1, and then deploy the agent.
You open the Foundry playground to test Agent1.
What does the playground use to ensure that the tests reflect production behavior?

A. a default configuration generated by the playground
B. the configuration of Agent1
C. the model ' s base behavior without any agent instructions or tools
D. the last saved configuration draft that was NOT deployed

Reveal Solution Discussion 0

Correct Answer: B 🗳️

Question #2

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Reveal Solution Discussion 0

Correct Answer:

Explanation:

Statement 1: An Azure Content Understanding in Foundry Tools analyzer returns results in the HTML format.
= No
Azure Content Understanding returns analysis results as structured output, typically JSON, not HTML.
Microsoft documentation states that the Content Understanding API returns analysis results in a structured JSON format.
Statement 2: The Content Understanding REST API analyzes content synchronously and returns results in the same response. = No Content Understanding analysis is asynchronous. The quickstart states that the response header includes an Operation-Location field, which is used to retrieve the results of the asynchronous analysis operation.
Statement 3: Azure Content Understanding in Foundry Tools can transform documents, images, audio, and video files into structured output. = Yes Microsoft describes Azure AI Content Understanding as processing documents, images, videos, and audio, and transforming them into user-defined output formats.

Question #3

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Reveal Solution Discussion 0

Correct Answer:

Explanation:

Statement 1: Fairness can be achieved by focusing solely on improving the overall accuracy of an AI model. = No Overall accuracy alone does not guarantee fairness. A model can have high overall accuracy while still producing biased or lower-quality outcomes for specific demographic groups. Fairness requires evaluating and reducing differences in model behavior across groups.
Statement 2: Evaluating AI system outputs to identify and reduce bias across demographic groups supports fairness. = Yes This statement is correct. The Microsoft responsible AI principle of fairness means AI systems should treat people fairly and avoid unfair bias. Evaluating outputs across demographic groups helps identify and reduce bias.
Statement 3: Ensuring fairness for an AI system means that all users always receive the same output from the system. = No Fairness does not mean identical outputs for all users. It means the system should avoid unfair bias and provide equitable treatment. Different users may receive different outputs when differences are relevant and appropriate.

Question #4

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?