Complete study guide for the AI-901 'Describe Artificial Intelligence concepts and capabilities' skill group (40–45%). Covers AI workloads, ML fundamentals, and responsible AI.
The 'Describe Artificial Intelligence concepts and capabilities' skill group covers 40–45% of the AI-901 exam. It tests three sub-skills: identifying the correct AI workload type for a given business scenario (computer vision, NLP, generative AI, document intelligence, agentic AI); defining and applying Microsoft's six responsible AI principles (Fairness, Reliability and Safety, Privacy and Security, Inclusiveness, Transparency, Accountability); and understanding machine learning fundamentals including supervised learning (classification, regression), unsupervised learning (clustering), and key evaluation metrics (precision, recall, F1 score, RMSE).
Key Azure services tested in this skill group include Azure Machine Learning for model training and deployment, Azure AI Services as the umbrella for Cognitive Services, and Azure AI Foundry as the unified development platform. Responsible AI questions frequently appear in scenario format: candidates must identify which principle is violated or upheld in a described situation. ML evaluation metric questions typically ask candidates to choose between precision, recall, and F1 based on the business tradeoff described.