AI-901 Skills Measured

This skill group covers the concepts behind AI solutions. Study Responsible AI, model components, generative AI, agentic AI, text analysis, speech, computer vision, image generation, information extraction, and when each workload is appropriate.

Know the six responsible AI principles Microsoft highlights: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. AI-901 tests recognition of these concerns in scenarios, not full governance-program design.

A fundamentals candidate should recognize supervised, unsupervised, and generative approaches, understand basic model components, and identify model deployment or configuration options at a high level. Azure Machine Learning appears as a foundational service, not as a deep MLOps exam topic.

Understand common workload clues. Azure AI Language supports text analysis. Azure AI Speech supports recognition and synthesis. Azure AI Vision supports image and visual input. Azure AI Document Intelligence and Content Understanding support extracting information from documents, images, audio, and video.

Generative AI questions may involve prompts, models, Azure OpenAI, and Retrieval-Augmented Generation (RAG). At the fundamentals level, know that RAG grounds model responses in retrieved information and helps reduce unsupported answers when designed well.

The current study guide includes implementing lightweight AI solutions by using Microsoft Foundry. Keep this beginner-focused: prompts, model interaction, simple chat clients, single-agent solutions, text and speech examples, vision inputs, image generation, and information extraction examples.