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AI-901

Exam AI-901: Microsoft Azure AI Fundamentals

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Outline from the official exam guide (opens in a new tab), as of April 15, 2026.

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Lessons

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Domain 1 · Weight 40-45%Not started0%

Identify AI concepts and capabilities

  1. Task 1.1Not started

    Describe principles of responsible AI

    QuizStudy with the guide

    Skills measured (6)
    • 1.1.1Describe considerations for fairness in an AI solution
    • 1.1.2Describe considerations for reliability and safety in an AI solution
    • 1.1.3Describe considerations for privacy and security in an AI solution
    • 1.1.4Describe considerations for inclusiveness in an AI solution
    • 1.1.5Describe considerations for transparency in an AI solution
    • 1.1.6Describe considerations for accountability in an AI solution
  2. Task 1.2Not started

    Identify AI model components and configurations

    QuizStudy with the guide

    Skills measured (3)
    • 1.2.1Describe how generative AI models work
    • 1.2.2Identify an appropriate AI model, based on capabilities
    • 1.2.3Identify appropriate model deployment options and configuration parameters
  3. Task 1.3Not started

    Identify AI workloads

    QuizStudy with the guide

    Skills measured (5)
    • 1.3.1Identify scenarios for common AI workloads, including generative and agentic AI, text analysis, speech, computer vision, and information extraction
    • 1.3.2Describe common text analysis techniques, including keyword extraction, entity detection, sentiment analysis, and summarization
    • 1.3.3Identify features and capabilities of speech recognition and speech synthesis
    • 1.3.4Identify features and capabilities of computer vision and image-generation models
    • 1.3.5Identify techniques to extract information from text, images, audio, and videos

Domain 2 · Weight 55-60%Not started0%

Implement AI solutions by using Microsoft Foundry

  1. Task 2.1Not started

    Implement generative AI apps and agents by using Foundry

    QuizStudy with the guide

    Skills measured (5)
    • 2.1.1Create effective system and user prompts for generative AI models
    • 2.1.2Deploy a model and interact with it in the Foundry portal
    • 2.1.3Create a lightweight chat client application by using the Foundry SDK
    • 2.1.4Create and test a single-agent solution in the Foundry portal
    • 2.1.5Create a lightweight client application for an agent
  2. Task 2.2Not started

    Implement AI solutions for text and speech by using Foundry

    QuizStudy with the guide

    Skills measured (3)
    • 2.2.1Build a lightweight application that includes text analysis
    • 2.2.2Respond to spoken prompts by using a deployed multimodal model
    • 2.2.3Build a lightweight application by using Azure Speech in Foundry Tools
  3. Task 2.3Not started

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

    QuizStudy with the guide

    Skills measured (3)
    • 2.3.1Interpret visual input in prompts by using a deployed multimodal model
    • 2.3.2Create new visual outputs by using generative models
    • 2.3.3Build a lightweight application that includes vision capabilities
  4. Task 2.4Not started

    Implement AI solutions for information extraction by using Foundry

    QuizStudy with the guide

    Skills measured (4)
    • 2.4.1Extract information from documents and forms by using Azure Content Understanding in Foundry Tools
    • 2.4.2Extract information from images by using Content Understanding
    • 2.4.3Extract information from audio and video by using Content Understanding
    • 2.4.4Build a lightweight application with information extraction capabilities by using Content Understanding

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Readiness

AI-901 readiness

0%

AI-901 readiness 0%, by domain
DomainWeightMastery
1Identify AI concepts and capabilities40-45%0%
2Implement AI solutions by using Microsoft Foundry55-60%0%

Fills in as you answer. Not a predicted score.

How readiness is calculated

Mastery per task statement uses your last 20 answers. Each older answer counts 0.9 times as much as the next. The warm-up questions at the start of a guided run do not count: they show what you knew before the lesson.

mastery = weighted share correct x min(answers, 5) / 5

Not started: no answers. Strong: 80% or more from 5 or more answers. Building: in between.

Domain mastery averages its task statements, with unstarted ones as 0.

Readiness averages the domains by their official weights, using the middle of any range.

It is not a predicted score or a pass probability.

Study the official path too

Microsoft

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About the exam

From the vendor’s own pages.

  • Microsoft states this for technical exams in general, not for AI-901 specifically.

  • Microsoft gives this for Fundamentals exams in general, not for AI-901 specifically.

  • This is general, and the AI-901 count is not published.

Ratings

5 out of 5 · 1 rating

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  • Learner5 out of 5Sep 29, 2026

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