Welcome to the AI-901: Azure AI Fundamentals Exam Prep Hub!

Welcome to the one-stop hub with information for preparing for the AI-901: Azure AI Fundamentals certification exam. The content for this exam helps you to demonstrate that “you have conceptual knowledge of AI solutions in Azure and the foundational technical skills to work with them”. You will also need “knowledge of Python coding syntax and programming techniques, and you should be familiar with Azure resources”.
Upon successful completion of the exam, you earn the Microsoft Certified: Azure AI Fundamentals certification.

This hub provides information directly here (topic-by-topic as outlined in the official study guide), links to a number of external resources, tips for preparing for the exam, practice tests, and section questions to help you prepare. Bookmark this page and use it as a guide to ensure that you are fully covering all relevant topics for the AI-901 exam and making use of as many of the resources available as possible.

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Audience profile (from Microsoft’s site)

As a candidate for this Microsoft Certification, you’re at the beginning of your career in AI solution development. These Microsoft certifications offer opportunities to demonstrate your understanding of machine learning, AI concepts, and Azure services, whether you are starting your career or advancing your skills in AI solution development. Both certifications are designed for candidates from technical and non-technical backgrounds—prior experience in data science or software engineering is not required, though familiarity with basic cloud concepts and client-server applications will be helpful.

For the AI-901, you should have foundational knowledge of AI workloads and understand the basic principles of AI and machine learning. And also, you should have foundational technical skills for working with AI solutions in Azure, conceptual knowledge of Azure-based AI solutions, and familiarity with Python coding syntax and programming techniques, as well as Azure resources.

You may be eligible for ACE college credit if you pass this certification. See ACE college credit for certification exams for details.

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Skills at a glance (as specified in the official study guide)

• Identify AI concepts and responsibilities (40–45%)
• Implement AI solutions by using Microsoft Foundry (55–60%)

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Topic-by-Topic Exam Content

[click a topic link to access the content and practice questions for that topic]

Identify AI concepts and capabilities (40–45%)

Describe principles of responsible AI

• Describe considerations for fairness in an AI solution
• Describe considerations for reliability and safety in an AI solution
• Describe considerations for privacy and security in an AI solution
• Describe considerations for inclusiveness in an AI solution
• Describe considerations for transparency in an AI solution
• Describe considerations for accountability in an AI solution

Identify AI model components and configurations

• Describe how generative AI models work
• Identify an appropriate AI model, based on capabilities
• Identify appropriate model deployment options and configuration parameters

Identify AI workloads

• Identify scenarios for common AI workloads, including generative and agentic AI, text analysis, speech, computer vision, and information extraction
• Describe common text analysis techniques, including keyword extraction, entity detection, sentiment analysis, and summarization
• Identify features and capabilities of speech recognition and speech synthesis
• Identify features and capabilities of computer vision and image-generation models
• Identify techniques to extract information from text, images, audio, and videos

Implement AI solutions by using Microsoft Foundry (55–60%)

Implement generative AI apps and agents by using Foundry

• Create effective system and user prompts for generative AI models
• Deploy a model and interact with it in the Foundry portal
• Create a lightweight chat client application by using the Foundry SDK
• Create and test a single-agent solution in the Foundry portal
• Create a lightweight client application for an agent

Implement AI solutions for text and speech by using Foundry

• Build a lightweight application that includes text analysis
• Respond to spoken prompts by using a deployed multimodal model
• Build a lightweight application by using Azure Speech in Foundry Tools

Implement AI solutions with computer vision and image-generation capabilities by using Foundry

• Interpret visual input in prompts by using a deployed multimodal model
• Create new visual outputs by using generative models
• Build a lightweight application that includes vision capabilities

Implement AI solutions for information extraction by using Foundry

• Extract information from documents and forms by using Azure Content Understanding in Foundry Tools
• Extract information from images by using Content Understanding
• Extract information from audio and video by using Content Understanding
• Build a lightweight application with information extraction capabilities by using Content Understanding

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AI-901 Practice Exams

• AI-901 Practice Exam #1 (30 questions with answers)
• AI-901 Practice Exam #2 (30 questions with answers)
• AI-901 Practice Exam #3 (30 questions with answers)
• AI-901 Practice Exam #4 (30 questions with answers)

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Important AI-901 Resources

• Link to the free, comprehensive, self-paced course on Microsoft Learn – Introduction to AI in Azure
• Link to the certification page: Microsoft Certified: Azure AI Fundamentals certification page
• Link to the study guide: Study guide for Exam AI-901: Microsoft Azure AI Fundamentals

• An overview of the AI-901 and how it compares to AI-900: AI-901 – Azure AI Fundamentals Exam Review by Tim Warner

• Multiple AI-901 related courses/videos: AI-901 Azure AI Fundamentals course and channel by Skilltech Club

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Good luck to you on your data journey!