Microsoft Azure AI Fundamentals Course: AI-900T00-A

Audience profile

Learning goals

Learners on the Microsoft Azure AI Fundamentals course are interested in learning about the Azure services that enable AI solutions. Students often aim to take the AI-900: Microsoft Azure AI Fundamentals exam and gain the AI-900 certification.

Applicable job roles

AI engineer, developer, data scientist.

Prerequisites

No specific experience is necessary before taking course. However, you will need a basic knowledge of computer technology and the Internet. A level of confidence with mathematics, such as being able to interpret charts, is also required. You’ll also benefit from a fundamental grasp of programming principles.

Students with no experience of Microsoft Azure may benefit from taking the following course first:

• Microsoft Azure Fundamentals Course (1 day): AZ-900T01-A

Course outline

Module 1: Introduction to AI

In this module, you’ll learn about common uses of artificial intelligence (AI), and the different types of workload associated with AI. You’ll then explore considerations and principles for responsible AI development.

Lessons

• Artificial Intelligence in Azure
• Responsible AI

After completing this module, students will be able to:

• Describe Artificial Intelligence workloads and considerations

Module 2: Machine Learning

Machine learning is the foundation for modern AI solutions. In this module, you’ll learn about some fundamental machine learning concepts, and how to use the Azure Machine Learning service to create and publish machine learning models.

Lessons

• Introduction to Machine Learning
• Azure Machine Learning

After completing this module, students will be able to:

• Describe fundamental principles of machine learning on Azure

Module 3: Computer vision

Computer vision is a the area of AI that deals with understanding the world visually, through images, video files, and cameras. In this module you’ll explore multiple computer vision techniques and services.

Lessons

• Computer Vision Concepts
• Computer Vision in Azure

After completing this module, students will be able to:

• Describe features of computer vision workloads on Azure

Module 4: Natural Language Processing

This module describes scenarios for AI solutions that can process written and spoken language. You’ll learn about Azure services that can be used to build solutions that analyze text, recognize and synthesize speech, translate between languages, and interpret commands.

Lessons

• Protect against security threats on Azure
• Secure network connectivity on Azure

After completing this module, students will be able to:

• Describe features of Natural Language Processing (NLP) workloads on Azure

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.

Lessons

• Conversational AI Concepts
• Conversational AI in Azure

After completing this module, students will be able to:

• Describe features of conversational AI workloads on Azure

Related courses

Azure AI engineer learning path

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