May 2025
Beginner to intermediate
228 pages
6h 4m
English
Content preview from Azure AI Fundamentals (AI-900) Study Guide
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Chapter 8. Features of Generative AI Workloads on Azure
About 15%–20% of the AI-900 exam is about features and scenarios for generative AI, which we’ll cover in this chapter. This includes understanding how models generate responses, create images, and write code snippets. We’ll also look at typical scenarios for generative AI, so you can connect theoretical knowledge with practical applications. This part of the exam isn’t just about knowing what generative AI is—it’s about recognizing its impact and relevance in real-world use cases.
Another key area on the exam involves responsible AI. This includes understanding the ethical implications of AI-generated content and the measures that Microsoft Azure takes to ensure its generative AI tools are used safely and responsibly. By mastering these topics, you’ll be well prepared to answer questions on how Azure’s generative AI services can be effectively and responsibly applied across various domains.
Understanding Generative AI
At its core, generative AI relies on models trained to understand and respond to language in ways that feel intuitive and humanlike. When you ask generative AI to generate content, it draws on massive amounts of data and applies mathematical algorithms to make this possible.
Generative AI has quickly become a centerpiece of the business world. It has attracted attention from industries across the board for its potential to streamline tasks, foster creativity, and drive productivity. Breakthrough applications ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.