Free Practice Questions for Microsoft Certified: Azure AI Fundamentals (AI-901) Certification
- Exam guide version:
- April 15, 2026
- Guide checked for updates:
- 9 Oct 2026
- Question bank created:
- 17 Sep 2026
- Question bank last updated:
- 23 Sep 2026
Study with 356 exam-style practice questions designed to help you prepare for the Microsoft Certified: Azure AI Fundamentals (AI-901). All questions are aligned with the latest exam guide and include detailed explanations to help you master the material.
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Key information about Microsoft Certified: Azure AI Fundamentals (AI-901)
- Multiple choice
- Matching
- True/False
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Beginning of career in AI solution development, conceptual knowledge of AI solutions in Azure, foundational technical skills, Python coding syntax and programming techniques, familiar with Azure resources
April 15, 2026
Exam Topics & Skills Assessed
Skills measured (from the official study guide)
1: Identify AI concepts and capabilities
1.1: 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
1.2: 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
1.3: 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
2: Implement AI solutions by using Microsoft Foundry
2.1: 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
2.2: 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
2.3: 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
2.4: 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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