Microsoft

Microsoft Azure AI Fundamentals

Foundational AI workloads, machine learning, computer vision, NLP, generative AI, and responsible AI on Azure.

AI-900
60Official questions
45 minOfficial duration
70%Practice target
100Questions available

Exam coverage

Skills you will practice

  • AI workloads, responsible AI, and Azure AI service selection
  • Machine learning fundamentals, features, training, and evaluation
  • Computer vision, natural language processing, and speech workloads
  • Generative AI, retrieval grounding, search, and agentic AI concepts

Practice exam

Build your session

Quick startOne click
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Questions10
160
Timer30 min
Off45 min

Difficulty

How to use this practice bank

Start with mixed, untimed sessions to identify weak areas. Then use focused difficulty sessions and gradually increase the question count and timer until you can sustain the pace of the official exam.

2026 Exam Guide

Microsoft Azure AI Fundamentals Study Guide

Current exam coverage, candidate guidance, important topics, and practical preparation advice for the AI-900 exam.

What Is Microsoft Azure AI Fundamentals?

Microsoft Azure AI Fundamentals is an entry-level AI certification earned through AI-900. It validates conceptual knowledge of artificial intelligence workloads and Azure AI services rather than deep model training expertise. Candidates should understand machine learning, computer vision, natural language processing, generative AI, responsible AI, and common Azure AI service categories.

The 2026 AI-900 scope reflects the importance of generative AI and responsible AI. Candidates should know when to use Azure AI services, Azure AI Foundry concepts, Azure AI Search, language and vision capabilities, speech services, and safety controls. The exam is foundational, but it still expects candidates to match real business requirements to the right AI capability.

Who Should Take This Exam?

AI-900 is useful for students, business analysts, product managers, developers, cloud beginners, data beginners, and technical stakeholders who need AI vocabulary on Azure.

No advanced machine learning background is required. Basic familiarity with cloud services and data concepts helps, and light Python or API awareness can make AI workflows easier to understand.

Exam Domains

AI Workloads and Responsible AI

Guide area

AI workload types, risks, responsible AI principles, and governance concerns.

Machine Learning

Guide area

Training, evaluation, features, supervised learning, and Azure ML concepts.

Vision, Language, and Speech

Guide area

Computer vision, OCR, NLP, translation, sentiment, and speech services.

Generative AI

Guide area

Prompts, grounding, retrieval, content safety, and agentic AI concepts.

Common Topics Covered

  • Responsible AI
  • Machine learning
  • Computer vision
  • OCR
  • NLP
  • Speech-to-text
  • Azure AI Search
  • Generative AI
  • Prompt grounding
  • Content safety

Study Tips

Focus on service selection. For each scenario, ask whether the requirement is prediction, classification, document extraction, text analysis, translation, speech, search, or generative AI.

Review responsible AI carefully. Safety, privacy, fairness, reliability, transparency, and accountability appear in many conceptual questions.

Practice Questions Overview

Certoga's AI-900 starter bank uses short, original scenarios to reinforce AI service selection and responsible AI reasoning. Use it with Microsoft Learn modules and basic Azure AI demos.

AI-900 Practice Exam & 2026 Study Guide | Certoga