Azure Mastery

Microsoft Certification AI-900

AI-900: Review the final outline. Move forward informed.

See your predicted score, follow a study plan based on your answers, and revisit topics you're starting to forget. It all runs on your device.

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AI-900 Retired Exam Practice & Next Steps — Microsoft Azure AI Fundamentals

Review the final AI-900 outline on iPhone or iPad, preserve the foundational skills you learned, and compare them with the current AI-901 requirements. Core study stays on-device and works offline; optional sync uses your private iCloud account. See every retired Microsoft exam and its successor on the retired exams hub.

The exam

What is the AI-900 exam?

AI-900 was the original exam for Microsoft Certified: Azure AI Fundamentals. Microsoft retired it on 30 June 2026, so it can no longer be scheduled. AI-901 is now the route to the Azure AI Fundamentals credential. This page and its question bank remain available as reference material for the former AI-900 outline.

The exam doesn't ask you to write Python or design a model architecture. It expects a clear conceptual map of AI workload types (computer vision, NLP, document processing, generative AI), the six responsible-AI principles, the difference between regression, classification, and clustering, and which Azure AI service matches a given scenario — Azure AI Vision, Azure AI Language, Azure AI Speech, Azure OpenAI, Microsoft Foundry. The May 2025 outline added significant generative-AI coverage, so a recent question bank matters more than for older fundamentals exams.

Microsoft last updated the AI-900 skills outline on 2 May 2025. Every question in Azure Mastery's AI-900 bank is mapped to that final outline. Read the archived official outline at learn.microsoft.com.

Skills measured · May 2025

AI-900 exam objectives

Five domains, with weights set by Microsoft's May 2025 update. Every domain summary below is paraphrased from the official skills outline; the bullet-level objectives in Azure Mastery are tagged so you always know which domain you're being tested on.

Aura presents a visual map of data, models, agents, and responsible AI skills.
AI & agent skill map

AI workloads and considerations15–20%

Explore key topics

The conceptual foundation. Identifies the four common AI workload types (computer vision, natural language processing, document processing, generative AI) with example scenarios for each, and walks through Microsoft's six guiding principles for responsible AI — fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. Expect scenario questions like "which responsible-AI consideration applies here?" Around 6–12 questions per sitting.

Fundamental principles of machine learning on Azure15–20%

Explore key topics

Common ML techniques (regression, classification, clustering, deep learning, the Transformer architecture) and core concepts (features and labels, training and validation datasets). Covers Azure Machine Learning capabilities: automated ML, the data and compute services, and the model management and deployment story. You don't write code — you identify the right technique for a given scenario. Around 6–12 questions.

Computer vision workloads on Azure15–20%

Explore key topics

Distinguishing image classification from object detection from optical character recognition (OCR) from facial detection — and matching each to the right Azure service. Covers the Azure AI Vision service and the Azure AI Face detection service: what each can do, what each is restricted from doing (Limited Access policies for Face), and which scenario maps to which. Around 6–12 questions.

Natural Language Processing (NLP) workloads on Azure15–20%

Explore key topics

The NLP scenario taxonomy: key phrase extraction, entity recognition, sentiment analysis, language modelling, speech recognition and synthesis, and translation. Maps each scenario to the right Azure tool — Azure AI Language for text analysis, Azure AI Speech for spoken-input/output. Around 6–12 questions.

Generative AI workloads on Azure20–25%

Explore key topics

The largest domain by typical question count, reflecting the May 2025 outline update. Covers what generative AI models are, common scenarios (chat, code, image generation, summarisation), and responsible-AI considerations specific to GenAI. Service coverage includes Microsoft Foundry, Azure OpenAI Service, and the Microsoft Foundry model catalog — what they offer and how they differ. Around 8–15 questions.

Designed for AI-900

How Azure Mastery preserves AI-900 coverage

Exam-specific practice

  • 340 AI-900 practice questions aligned to the published skills outline.
  • Coverage follows the official five domains (AI workloads, ML on Azure, computer vision, NLP, generative AI).
  • Practise decisions from the exam outline with scenarios and interactive questions.

Predicted score

  • Exam IQ predicts your AI-900 score on-device after roughly 30 questions.
  • A confidence range shows how stable the prediction is.
  • See which exam objectives need the most work.

Adaptive study plan

  • Your study plan updates as you answer questions.
  • Missed topics return sooner; consistently mastered topics appear less often.
  • Sessions focus on the gaps most likely to help you reach the 700 pass score.

Knowledge decay

  • Track which topics you're starting to forget.
  • Get reminders to revisit those topics before exam day.
  • Weak-spot sessions bring fading topics back into practice.

Exam rehearsal

  • Practise staying focused through a full 45-minute session.
  • Original questions follow the published domain weighting.
  • Microsoft controls the live interface and exact question mix.

Answer Coach

  • Every answer has a written explanation, with reasons for individual options where available.
  • See why you missed an answer, how the options differ, and what to remember.
  • On supported devices, optional AI can reword notes while checking them against the written explanations.

Aura guidance

  • Aura suggests what to do after each session.
  • Recaps show your progress and which topics to practise next.

Private by design

  • Practice, scoring, readiness, and coaching run on-device.
  • You don't need an Azure Mastery account or a server to process your study data.
  • Optional sync uses your private iCloud account.

2-week revision plan

Suggested AI-900 study plan

Use this two-week plan for historical AI-900 revision. Finish by comparing the retired outline with AI-901 and moving to its current practice bank.

  1. AI workloads and responsibility

    • Identify common AI workloads.
    • Review the six responsible AI principles.
    • Practise matching principles to scenarios.
  2. Machine learning concepts

    • Compare regression, classification and clustering.
    • Distinguish deep learning and Transformer models.
    • Match each approach to a suitable scenario.
  3. Vision and language

    • Compare Vision, Face and Document Intelligence.
    • Distinguish Language and Speech capabilities.
    • Review service-selection mistakes.
  4. Generative AI

    • Explore Microsoft Foundry and Azure OpenAI.
    • Review the model catalogue.
    • Consider responsible AI for generative workloads.
  5. Target weaker topics

    • Run Focus Weak Spots sessions.
    • Revisit explanations for missed questions.
    • Review topics that have faded from memory.
  6. Historical rehearsal

    • Complete two timed, 45-minute simulator sessions.
    • Review the explanations after each run.
    • Record concepts to revisit.
  7. Compare the outlines

    • Review AI-901's Foundry requirements.
    • Explore its Python-example requirements.
    • Identify what you need to study next.
  8. Move to AI-901

    • Open the AI-901 practice bank.
    • Use its study plan to cover the gaps.
    • Choose an exam after reviewing the current route.

Inside the app

Nine interactive practice formats, on iPhone

Azure Mastery has nine interactive formats for exam practice. The examples below show original AI-900 practice questions in Azure Mastery on iPhone and iPad. The exam simulator uses timed sessions with the published domain weights. Microsoft's live interface and question mix may differ.

How many principles are included in Microsoft's Responsible AI framework?

  • 4
  • 5
  • 6
  • 8

Multiple choice

An original AI-900 practice question with one correct answer. The app explains every option after you answer.

Exam-specific sample

Which models are available through Azure OpenAI Service? (Select all that apply)

  • GPT-4o
  • DALL-E
  • Whisper
  • Azure SQL
  • Text-embedding-ada-002

Multi-select

An original AI-900 multi-select question. Select all the correct options to earn the mark.

All-or-nothing

Drag to match

An original AI-900 ordering question you can answer by touch on iPhone and iPad.

Interactive item

Hotspot

An original AI-900 question with a visual prompt, designed for touch on iPhone and iPad.

Tap target

Case studies

An original AI-900 case study with several questions about the same requirements and environment.

Multi-question

Answer Coach

Answer Coach explains why the answer is correct and, where available, why each option is right or wrong. It helps you understand a mistake and remember the distinction. Read explanations after each question or at the end of a practice test. On supported devices, optional AI can reword a note on your device after checking it against the written guidance.

App exclusive

Frequently asked

AI-900 FAQs

Can I still take the AI-900 exam?

No. Microsoft retired AI-900 on 30 June 2026, so it can no longer be scheduled. AI-901 is now the exam route to the Azure AI Fundamentals credential.

What replaced AI-900?

AI-901 replaced AI-900 on 1 July 2026. It remains the route to Microsoft Certified: Azure AI Fundamentals and adds a more implementation-oriented focus on Microsoft Foundry and Python examples.

What happens if I already passed AI-900?

An Azure AI Fundamentals credential earned through AI-900 remains on your Microsoft Learn transcript. AI-900 itself is retired and cannot be retaken.

Are AI-900 practice questions still useful?

Yes, as reference material for core AI, machine-learning, vision, language, and responsible-AI concepts. New candidates should study the current AI-901 outline and use the AI-901 bank for exam readiness.

AI-900 vs AI-102 — which should I take first?

AI-900 first, unless you already build AI applications professionally. AI-900 is the conceptual map: it teaches you the vocabulary (image classification vs object detection, key phrase extraction vs entity recognition, regression vs classification, the Foundry model catalog) without expecting you to write code. AI-102 is the role-based Associate exam — it expects hands-on Python, REST API calls against Azure AI services, and prompt-engineering against Azure OpenAI. Most candidates pass AI-900 in a few weeks, then spend two to three months on AI-102.

Is AI-900 worth taking if I'm not technical?

Yes — that's a large part of the audience. Microsoft positions AI-900 for both technical and non-technical candidates: solution consultants, sales engineers, technical PMs, business stakeholders evaluating Azure AI procurement, and anyone wanting a credible answer to "which Azure AI service should we use for this?" The exam doesn't ask you to write Python. It asks you to recognise scenarios — "which Azure AI service is best suited for redacting PII from a document?" or "which guiding principle of responsible AI applies here?" — and pick the correct option.

Is Azure Mastery free for AI-900 prep?

The app is free to download and includes a free allowance of AI-900 questions so you can try every feature. The full bank of 340 AI-900 practice questions unlocks with a one-time exam-pack purchase, or you can unlock every exam in the catalogue with a subscription or a one-time lifetime upgrade.

Does AI-900 practice work offline?

Yes. Question practice, scoring, and the readiness prediction all run on-device, so you can study on a flight or a commute with no connection. No account is required, and your study data stays on your device with optional private iCloud sync.

Is there an AI-900 practice test mode?

Yes — timed practice sessions use original, blueprint-aligned questions, published timing guidance, and supported interactive item types. Adaptive study sessions and Focus Weak Spots then target the domains where your accuracy is lowest.

Free study guides

Free guides that pair with AI-900

Where AI-900 fits

Certification paths that start with AI-900

AI-900 is the foundational entry point for Microsoft's AI and Data Science role-based tracks. It's optional but strongly recommended — Microsoft markets it as preparation for the Azure AI Engineer Associate and Azure Data Scientist Associate paths, even though it's not a formal prerequisite. If your interest is general Azure infrastructure, look at AZ-900 (Azure Fundamentals) instead.

Azure AI Engineer path

Associate tier
  1. AI-900 Fundamentals
  2. AI-102 AI Engineer Associate

Azure Data Scientist path

Associate tier
  1. AI-900 Fundamentals
  2. DP-100 Data Scientist Associate

Generative AI & agent specialisation

Associate / specialty
  1. AI-900 Fundamentals
  2. AI-102 recommended Associate
  3. or AB-620 AI Agent Builder
  4. Generative-AI specialist role-ready

Review AI-900 or move to AI-901

Keep 340 retired-outline AI-900 questions for reference, or use Azure Mastery's current AI-901 bank and adaptive study plan for the active Azure AI Fundamentals route.

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