Course data sheet
Microsoft Azure AI Fundamentals (AI-900T00)
HQ6Y9S
Table of Contents
Overview
This course introduces fundamental concepts related to artificial intelligence (AI) and the services in Microsoft Azure used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and provide the ability to identify Azure services to support them. The course is a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform. The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth.
Audience
The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solutions made possible with artificial intelligence (AI), and the services on Microsoft Azure used to create them.
Prerequisites
- Students must be familiar with computers and web browsers.
- Students do not need to have any experience with Microsoft Azure, but the course assumes a basic level of familiarity with computer technology and the internet.
- Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts.
- The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles is helpful.
Objectives
After completing this course, you should be able to:
- 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 conversational AI workloads on Azure
Course outline
| Module 1: Introduction to AI | In this module, students learn about common uses of artificial intelligence (AI) and the different types of workload associated with AI. Students explore considerations and principles for responsible AI development. |
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| Module 2: Machine Learning | Machine learning is the foundation for modern AI solutions. In this module, students learn about fundamental machine learning concepts and how to use the Azure Machine Learning service to create and publish machine learning models. |
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| Module 3: Computer Vision | Computer vision is the area of AI that deals with understanding the world visually, through images, video files, and cameras. In this module, students explore multiple computer vision techniques and services. |
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| Module 4: Natural Language Processing | This module describes scenarios for AI solutions that can process written and spoken language. Students learn Azure services to build solutions to analyze text, recognize and synthesize speech, translate between languages, and interpret commands. |
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| Module 5: Conversational AI | Conversational AI enables users to engage in a dialog with an AI agent, or *bot*, through communication channels such as email, webchat interfaces, social media, and others. This module describes some basic principles for working with bots and gives you an opportunity to create a bot that can respond intelligently to user questions. |
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a50014632enw, HQ6Y9S A.00, January 2026