Five domains, with weights set by Microsoft's May 2025 update. Every domain summary below is paraphrased from the official skills outline; the bullet-level objectives in Azure Mastery are tagged so you always know which domain you're being tested on.
AI workloads and considerations15–20%
The conceptual foundation. Identifies the four common AI workload types (computer vision, natural language processing, document processing, generative AI) with example scenarios for each, and walks through Microsoft's six guiding principles for responsible AI — fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. Expect scenario questions like "which responsible-AI consideration applies here?" Around 6–12 questions per sitting.
Fundamental principles of machine learning on Azure15–20%
Common ML techniques (regression, classification, clustering, deep learning, the Transformer architecture) and core concepts (features and labels, training and validation datasets). Covers Azure Machine Learning capabilities: automated ML, the data and compute services, and the model management and deployment story. You don't write code — you identify the right technique for a given scenario. Around 6–12 questions.
Computer vision workloads on Azure15–20%
Distinguishing image classification from object detection from optical character recognition (OCR) from facial detection — and matching each to the right Azure service. Covers the Azure AI Vision service and the Azure AI Face detection service: what each can do, what each is restricted from doing (Limited Access policies for Face), and which scenario maps to which. Around 6–12 questions.
Natural Language Processing (NLP) workloads on Azure15–20%
The NLP scenario taxonomy: key phrase extraction, entity recognition, sentiment analysis, language modelling, speech recognition and synthesis, and translation. Maps each scenario to the right Azure tool — Azure AI Language for text analysis, Azure AI Speech for spoken-input/output. Around 6–12 questions.
Generative AI workloads on Azure20–25%
The largest domain by typical question count, reflecting the May 2025 outline update. Covers what generative AI models are, common scenarios (chat, code, image generation, summarisation), and responsible-AI considerations specific to GenAI. Service coverage includes Microsoft Foundry, Azure OpenAI Service, and the Microsoft Foundry model catalog — what they offer and how they differ. Around 8–15 questions.
