Azure AI Fundamentals

Take this free Microsoft Learn path if you want a fast, vendor-specific orientation to AI on Azure and you are comfortable with a little Python — but know that, as of mid-2026, the content and the related certification are in transition. The catalog URL now resolves to a redesigned path, 'Get started with AI applications and agents on Azure' (6 modules, beginner level), built around the new Microsoft Foundry portal and covering generative AI and agents, text analysis, speech, computer vision, and information extraction. The companion AI-900 exam retires on June 30, 2026 and is replaced by AI-901 (already in beta); the legacy AI-900 self-paced path is now marked deprecated, so newcomers aiming for the certification should plan around AI-901. The path itself is genuinely free and well-structured, and the exam is widely considered the easiest of Microsoft's fundamentals tests. The honest limitation, echoed by reviewers, is that this is conceptual awareness training, not hands-on engineering: it teaches you to recognize and discuss Azure AI services, not to build production systems.

Free, credible, and well-structured for absolute beginners who want Azure-specific AI literacy, but two caveats make it conditional: (1) the certification it maps to (AI-900) retires June 30, 2026 and is replaced by AI-901, so cert-seekers should target AI-901, and (2) the refreshed path now assumes basic Python and computing knowledge, so true non-coders may find parts heavier than the old AI-900 material.

Best for: Beginners and career-switchers who want a free, structured introduction to AI concepts as implemented on Microsoft Azure/Foundry; cloud, IT-operations, project-management, sales, and business-strategy professionals who need to understand and discuss Azure AI services; and anyone planning to pursue the Azure AI Fundamentals credential (now via AI-901) as a stepping stone toward Azure AI Engineer or Data Scientist tracks.

Skip if: People who already work with Azure AI/ML day to day (the content will be far below their level), engineers wanting deep hands-on model-building or math (try fast.ai or Andrew Ng's ML/Deep Learning specializations), and learners who want a vendor-neutral foundation rather than Microsoft-Azure-specific tooling.