Study Guide: Azure AI Fundamentals (AI-900)

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Last updated: 2025-07-22

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A landing zone is a general cloud framework that sets up the core structure for all workloads. Each use case (like an app, data pipeline, or API) then builds on top of this framework, using the same environments (Dev → Test → UAT → Prod) and CI/CD pipelines to move code safely into production. It’s general by design, but applied per use case.

Note

The questions and answers provided in this study guide are for practice purposes only and are not official practice questions. They are intended to help you prepare for the AI-900 Microsoft certification exam. For additional preparation materials and the most up-to-date information, please refer to the official Microsoft documentation. Read all here Study guide for Exam AI-900: Microsoft Azure AI Fundamentals

How we move from basic coding all the way to AI agents?

flowchart LR
    A[Scripting: Line-by-line instructions] --> B[Machine Learning: Packages + statistical foundations]
    B --> C[LLMs: Reasoning, understanding, human-like responses]
    C --> D[Agents: LLMs with ability to act]

    %% Styling
    classDef step fill:#4a90e2,stroke:#333,stroke-width:2px,color:#fff,font-weight:bold;
    class A,B,C,D step;

    %% Extra notes
    A:::step
    B:::step
    C:::step
    D:::step

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More details about it here (Click to expand)

• We all start with scripting, no matter the language, it’s the first step. Simple/complex instructions, written line by line, to get something done
• Then comes machine learning. At this stage, we’re not reinventing the math, we’re leveraging powerful packages built on deep statistical and mathematical foundations. These tools let us automate smarter processes, like reviewing claims with predictive analytics. You’re not just coding anymore; you’re building systems that learn and adapt.
• LLMs. This is what most people mean when they say AI. Think of yourself as the architect, and the LLM as your strategic engine. You can plug into it via an API, a key, or through integrated services. It’s not just about automation, it’s about reasoning, understanding, and generating human-like responses.
• And finally, agents. These are LLMs with the ability to act. They don’t just respond, they take initiative. They can create code, trigger workflows, make decisions, interact with tools, with other agents. It’s where intelligence meets execution

Content

• Artificial Intelligence: Sample Questions and Answers
• Machine Learning: Sample Questions and Answers
• Computer Vision: Sample Questions and Answers

Skills measured

• Describe Artificial Intelligence workloads and considerations
• Describe fundamental principles of machine learning on Azure
• Describe features of computer vision workloads on Azure
• Describe features of Natural Language Processing (NLP) workloads on Azure
• Describe features of generative AI workloads on Azure

Tip

Check out Certification poster

Badge from Credly

Refresh Date: 2025-08-05