AI-901: Introduction to AI in Azure

Your Complete Study Guide for the Microsoft Azure AI Fundamentals Certification

These study notes summarise Microsoft Learn material for Exam AI-901. For the official skills measured, see the Microsoft Learn study guide for Exam AI-901.

A beginner-friendly, topic-based study guide for the Microsoft AI-901 (Azure AI Fundamentals Beta) certification. Covers AI concepts, generative AI and agents, natural language processing, speech, computer vision, and information extraction - both conceptually and practically on Azure using Microsoft Foundry.

In this guide

1. 1Introduction to AI and AzureStart here. This chapter covers what AI actually is, the six core AI workloads tested in AI-901, the principles of responsible AI, what Microsoft Azure is, and how Microsoft Foundry brings it all together as the platform for building AI solutions.35 min read
2. 2Machine Learning FundamentalsUnderstand the core machine learning concepts tested in AI-901: supervised, unsupervised, and reinforcement learning, regression vs classification vs clustering, how models are trained and evaluated, and where Azure Machine Learning fits in. This module fills the foundational ML knowledge the other modules assume.11 min read
3. 3Generative AI and AgentsUnderstand how large language models work, how prompts shape their outputs, and how AI agents extend models with tools and actions. This chapter also covers how to work with generative AI models and build agents in Microsoft Foundry.20 min read
4. 4Natural Language Processing and Text AnalysisExplore how AI makes sense of human language. This chapter covers tokenization, how text is statistically analyzed, semantic language models, and how Azure Language in Microsoft Foundry enables practical text analysis tasks like sentiment analysis, entity extraction, and summarization.13 min read
5. 5AI and SpeechLearn how AI converts spoken language to text and text back to speech. This chapter covers the full speech recognition and synthesis pipelines, real-world use cases, and how to use Azure Speech in Microsoft Foundry to build voice-enabled applications.13 min read
6. 6Computer VisionLearn how AI interprets visual information from images and video. This chapter covers the four core CV tasks (image classification, object detection, semantic segmentation, and multimodal analysis), how CNN and Vision Transformer architectures learn from data, diffusion-based image and video generation, and Azure AI Vision capabilities in Microsoft Foundry.12 min read
7. 7AI-Powered Information ExtractionLearn how AI unlocks structured data from unstructured sources. This chapter covers the full OCR pipeline, field extraction and mapping techniques, and how Azure Document Intelligence and Azure Content Understanding in Foundry automate document processing at scale.14 min read
8. 8Responsible AI in PracticeGo beyond the six principles and understand how responsible AI works in practice. This module covers how to apply each principle to real scenarios, the Azure tools that enforce them, impact assessments, human oversight, and the governance questions the exam uses to test accountability and transparency.15 min read