Free sections from Ultra Transcenders AI-901: Microsoft Azure AI Fundamentals, on the comparisons and decisions the exam keeps asking about.
Fairness, reliability and safety, privacy and security, inclusiveness, transparency and accountability, and how to tell them apart in a scenario.
How guardrails, system messages, grounding and user experience design reduce harm in a generative AI solution.
What happens between a prompt and a response, and how inference differs from training.
Which model setting controls randomness, which controls length and cost, and which ones are not set at deployment.
How to recognise each AI workload from a scenario.
Agents as model plus instructions, knowledge and tools, and the auto, required and none tool_choice values.
Speech to text, text to speech, translation, batch transcription and speaker recognition compared.
How analyzers turn documents, images, audio and video into structured JSON, and how to call them from code.