[Domain Mastery] AI-900 Guide: Domain #5 ~ Describe Features of Generative AI Workloads on Azure
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Summary
This is where AI moves from analyzing data to creating content, reasoning, and assisting users in real time.
In this episode of Programmer’s Guide – Domain Mastery, we take a deep dive into generative AI workloads on Azure, a rapidly evolving and high-impact domain in the AI-900: Microsoft Certified: Azure AI Fundamentals certification.
This domain helps you understand how modern AI systems generate text, images, and insights—and how Azure provides the tools to build and manage these experiences.
In this deep dive, we cover:
- Core concepts of generative AI, including large language models (LLMs) and prompt-based interactions
- Azure OpenAI Service and how it enables generative AI solutions
- Prompt engineering fundamentals and how prompts influence model behavior
- Retrieval-Augmented Generation (RAG) and how it improves response accuracy using external data
- Responsible AI considerations including content filtering, safety, and governance
- Real-world use cases such as chatbots, copilots, content generation, and knowledge assistants
We also break down:
- How generative AI scenarios appear in exam questions
- Common confusion between traditional AI workloads and generative AI capabilities
- Simple mental models to identify when and how to use generative AI effectively
This episode is designed to help you understand how generative AI systems work—and how to apply them with clarity and confidence.
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