AI-900: Microsoft Azure AI Fundamentals

AI-900 validates foundational knowledge of AI concepts, machine learning, and Azure AI services. It is designed for technical and non-technical candidates who need to understand when to use common AI workloads and which Azure services support them.

⏱45 min❓40-60🎯700/1000 to pass 💰Varies by region🎓Fundamentals🏢Pearson VUE

Retirement Notice

Microsoft lists AI-900: Microsoft Azure AI Fundamentals and the related certification as retiring on June 30, 2026. This track is expected to be replaced by AI-901: Azure AI Fundamentals, with a stronger emphasis on Microsoft Foundry, generative AI apps, and agents.

Use these AI-900 notes if you are targeting the current exam before retirement. If your exam date is after June 2026, verify whether AI-901 has fully replaced AI-900 before booking.

Currently Studying ⏳

Target Date: June 2026

Notes Prepared: April 2026 | Last Updated: 2026-04-06

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Exam Type

This is a fundamentals exam. Expect concept recognition, scenario-to-service matching, and responsible AI principles rather than implementation-heavy SDK or architecture questions.

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What the Exam Covers

Domain	Weight	Focus
Domain 1: AI workloads and considerations	15-20%	Workload types and responsible AI principles
Domain 2: Machine learning on Azure	15-20%	Regression, classification, clustering, deep learning, Transformers, Azure ML
Domain 3: Computer vision workloads	15-20%	Image classification, object detection, OCR, face detection, Azure AI Vision
Domain 4: NLP workloads	15-20%	Key phrase extraction, entities, sentiment, speech, translation, Azure AI Language and Speech
Domain 5: Generative AI workloads	20-25%	Generative AI models, responsible GenAI, Azure AI Foundry, Azure OpenAI

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Study Progress

AI-900 Azure AI Fundamentals Study Progress

0/90%

Domain 1: AI workloads and considerations (15-20%) ↗

• Common AI workloads: vision, NLP, document processing, generative AI
• Responsible AI: fairness, reliability, privacy, inclusiveness, transparency, accountability

Domain 2: Machine learning on Azure (15-20%) ↗

• Regression, classification, clustering, deep learning, Transformers
• Features, labels, training data, validation data
• Automated ML, data and compute, model management and deployment

Domain 3: Computer vision workloads (15-20%) ↗

• Image classification, object detection, OCR, face detection and analysis
• Azure AI Vision and Azure AI Face detection capabilities

Domain 4: NLP workloads (15-20%) ↗

• Key phrases, entities, sentiment, language modeling, speech, translation
• Azure AI Language and Azure AI Speech capabilities

Domain 5: Generative AI workloads (20-25%) ↗

• Generative AI models, scenarios, and responsible AI risks
• Azure AI Foundry, Azure OpenAI, and Foundry model catalog

Reviewed exam guide and traps ↗

Reviewed cheatsheet ↗

Reviewed exam tips ↗

Ready for exam

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Official Resources

• AI-900 Certification Page
• AI-900 Study Guide
• Learning Path: Introduction to AI on Azure
• Practice Assessment
• Exam Sandbox
• Lab Simulations
• Microsoft Fundamentals Exam Readiness Video

Additional Reading

• Create prompts for generative AI training tools
• AI concepts learning path
• Get started with AI applications and agents on Azure
• AI-900 community series

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