AI-901 Azure AI Fundamentals Study Guide

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AI-901 Azure AI Fundamentals Study Guide

The  AI-901 Microsoft Certified Azure AI Fundamentals certification exam introduces the foundational concepts of building AI applications and agents using Microsoft Foundry. It focuses on the essential principles of AI development, making it ideal for beginners who are looking to understand AI technologies and build applications on Microsoft platforms. The beta exam will be available in April 2026, with training expected in March 2026 and the full exam launching in June 2026.

For more information about the AI-901 exam, you can check out this exam skills outline. This study guide will provide comprehensive review materials to help you pass the exam successfully.

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AI-901 Exam Domains

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AI-901 Study Materials

Before attempting the AI-901 Microsoft Certified Azure AI Fundamentals exam, it is highly recommended to review the following study materials. These resources are designed to help candidates understand the key concepts, tools, and services that are commonly evaluated in the certification. By studying these materials in advance, candidates can strengthen their knowledge of machine learning operations, automation, and deployment practices within the Microsoft ecosystem.

 

Azure Services to Focus on for the AI-901 Exam

Here is the list of Azure services that you have to focus on for your upcoming AI-901 Microsoft Certified Azure AI Fundamentals exam:

Azure Cognitive & AI Services

  • Azure AI Vision — image classification, object detection, optical character recognition (OCR) fundamentals using Azure AI Vision capabilities.
  • Azure AI Language & NLP — essential natural language processing tasks such as sentiment analysis, key phrase extraction, and entity recognition with Azure AI Language service.
  • Azure AI Speech — introductory speech recognition and text‑to‑speech functionality for building basic voice‑enabled solutions
  • Azure OpenAI & Generative AI Services — features and capabilities of Azure AI Foundry and Azure OpenAI (generative AI tools on Azure).

Microsoft Foundry

  • Foundry Resources & Project Setup — configure Microsoft Foundry for building AI applications, including setting up project environments, deploying foundation models, and managing prompt versioning.
  • AI Model Management — deploy and monitor foundation models, manage prompt versioning, and evaluate metrics such as latency, throughput, and token usage within Microsoft Foundry.
  • AI Workflows in Foundry — design and manage multistep reasoning workflows, ensuring smooth operation within Microsoft Foundry environments.

Azure Machine Learning Fundamentals

  • Azure Machine Learning basics — fundamental understanding of machine learning principles on Azure, including supervised and unsupervised learning concepts and the role of automated machine learning (AutoML).
  • Model concepts & capabilities — overview of model training, evaluation, and the purpose of compute and data services in Azure ML.

Responsible AI & AI Workload Considerations

  • Responsible AI principles — fairness, reliability, security, privacy, and transparency in AI solutions.
  • AI workloads identification — recognize common AI scenarios (machine learning, computer vision, NLP, generative AI) and understand basic guidance for choosing appropriate Azure services.

Supportive Azure Capabilities

  • Azure Bot Services Concepts — foundational knowledge of creating conversational AI (chatbots) using Azure Bot Services as a scenario for natural language and AI integration.
  • Azure Cloud Fundamentals — basic awareness of cloud concepts, identity, and compute as they relate to deploying and consuming Azure AI services.

 

AI-901 Key Exam Topics by Domain

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AI-901 Important Skills to Focus on

  • AI Service Integration — integrate Azure Cognitive Services such as vision, speech, and language APIs into AI solutions to build intelligent applications with computer vision, text analytics, and speech recognition capabilities.
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  • Model Deployment and Monitoring — deploy AI models using Microsoft Foundry and monitor their performance with metrics such as latency, throughput, and token usage, ensuring the models perform as expected in production.
  • Generative AI Model Management — implement generative AI solutions, including configuring foundation models, managing prompt versioning, and optimizing inference configurations for scalable AI workloads.
  • Responsible AI Practices — evaluate and ensure AI models comply with responsible AI principles, focusing on fairness, transparency, and accountability, and applying these principles to AI applications.

 

Validate Your AI-901 Exam Readiness

If you feel confident after going through the suggested materials above, it’s time to put your knowledge of different Azure concepts and services to the test. For top-notch practice exams, consider using the Tutorials Dojo’s AI-901 Microsoft Certified Azure AI Fundamentals Practice Exams.

These practice tests cover the relevant topics that you can expect from the real exam. It also contains different types of questions, such as single-choice, multiple-response, hotspot, yes/no, and drag-and-drop. Every question on these practice exams has a detailed explanation and adequate reference links that help you understand why the correct answer is the most suitable solution. After you’ve taken the exams, it will highlight the areas you need to improve. Together with our cheat sheets, we’re confident that you’ll be able to pass the exam and have a deeper understanding of how Azure works.

TD AI-901 Azure AI Fundamentals Practice Exams

 

AI-901 Sample Practice Test Questions:

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For more Azure practice exam questions with detailed explanations, check out the Tutorials Dojo Portal:

Azure Practice Exams

Azure Practice Exams

 

 

Final Remarks

Success in the AI-901 exam requires a solid understanding of the core AI services and foundational principles of AI development on Azure. Focus your preparation on the official Microsoft Learn materials, and enhance your understanding through hands-on practice with services like Azure Cognitive Services, Microsoft Foundry, and Azure Machine Learning. Practice exams are also valuable for evaluating your progress and pinpointing areas that need further attention. By following this targeted approach, you’ll be well-equipped to earn the Microsoft Certified Azure AI Fundamentals certification. Best of luck with your studies!

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Written by: Lois Angelo Dar Juan

Lois Angelo Dar Juan is a licensed Electronics Engineer, an AWS-certified professional, and currently a Cloud Engineer at Tutorials Dojo, with a passion for emerging technologies, cloud computing, and IT automation. He continuously seeks opportunities to learn and innovate, applying his expertise to solve problems efficiently.

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