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Introduction to AI in Azure

This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach...

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$675 USD
Duration 1 day
Course Code AI-900T00
Available Formats Classroom, Virtual

Overview

This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be 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 the ability to identify Azure services to support them. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform (https://azure.com/learn). 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 Profile

The Introduction to AI in Azure course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don’t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. 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 will be helpful.

Skills Gained

After completing this course, you will 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

Prerequisites

Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services.
Specifically:

  • Experience using computers and the internet.
  • Interest in use cases for AI applications and machine learning models.
  • A willingness to learn through hands-on exploration.

Course Details

Outline

  • Overview of AI concepts
    • Introduction to AI
    • Generative AI and agents
    • Text and natural language
    • Speech
    • Computer vision
    • Information extraction
    • Responsible AI
    • Exercise - Explore a simple AI agent
    • Module assessment
  • Get started with AI in Microsoft Foundry
    • What is an AI application?
    • Components of an AI application
    • Microsoft Foundry for AI
    • Get started with Foundry
    • Understand Azure
    • Exercise - Explore AI in Microsoft Foundry
    • Knowledge check
  • Introduction to machine learning concepts
    • Machine learning models
    • Types of machine learning model
    • Regression
    • Binary classification
    • Multiclass classification
    • Clustering
    • Deep learning
    • Exercise - Explore machine learning scenarios
    • Module assessment
  • Get started with machine learning in Azure
    • Define the problem
    • Get and prepare data
    • Train the model
    • Use Azure Machine Learning studio
    • Integrate a model
    • Exercise - Explore Automated Machine Learning in Azure Machine Learning
    • Module assessment
  • Introduction to generative AI and agents
    • Large language models (LLMs)
    • Prompts
    • AI agents
    • Exercise - Explore generative AI agent scenarios
    • Module assessment
  • Get started with generative AI in Microsoft Foundry
    • Understand generative AI applications
    • Understand generative AI development in Foundry
    • Understand Foundry's model catalog
    • Understand Foundry capabilities
    • Understand observability
    • Exercise - Explore generative AI in Microsoft Foundry
    • Module assessment
  • Introduction to text analysis concepts
    • Tokenization
    • Statistical text analysis.
    • Semantic language models
    • Exercise - Explore text analytics
    • Module assessment
  • Get started with natural language processing in Microsoft Foundry
    • Understand natural language processing on Azure
    • Understand Azure Language's text analysis capabilities
    • Azure Language's conversational AI capabilities
    • Azure Translator capabilities
    • Get started in Microsoft Foundry
    • Exercise - Analyze text in Microsoft Foundry
    • Module assessment
  • Introduction to AI speech concepts
    • Speech-enabled solutions
    • Speech recognition
    • Speech synthesis
    • Exercise - Explore an AI speech scenario
    • Module assessment
  • Get started with speech in Microsoft Foundry
    • Understand speech recognition and synthesis
    • Get started with speech on Azure
    • Use Azure Speech
    • Exercise - Explore Speech in Microsoft Foundry
    • Module assessment
  • Introduction to computer vision concepts
    • Computer vision tasks and techniques
    • Images and image processing
    • Convolutional neural networks
    • Vision transformers and multimodal models
    • Image generation
    • Exercise - Explore a computer vision scenario
    • Module assessment
  • Get started with computer vision in Microsoft Foundry
    • Understand Foundry Tools for computer vision
    • Understand Azure Vision Image Analysis capabilities
    • Understand Azure Vision's Face service capabilities
    • Get started in Microsoft Foundry portal
    • Exercise - Analyze images in Microsoft Foundry
    • Module assessment
  • Introduction to AI-powered information extraction concepts
    • Overview of information extraction
    • Optical character recognition (OCR)
    • Field extraction and mapping
    • Exercise - Explore AI information extraction
    • Module assessment
  • Get started with AI-powered information extraction in Microsoft Foundry
    • Azure AI services for information extraction
    • Extract information with Azure Vision
    • Extract multimodal information with Azure Content Understanding
    • Extract information from forms with Azure Document Intelligence
    • Create a knowledge mining solution with Azure AI Search
    • Exercise - Extract information
    • Module assessment
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Objectives

Schedule

5 options available

  • Feb 16, 2026 - Feb 16, 2026 (1 day)
    Live Virtual | 9:00AM 5:00PM EST
    Language English
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    Live Virtual |9:00AM 5:00PM EST
    Live Virtual | 9:00AM 5:00PM EST
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  • Mar 17, 2026 - Mar 17, 2026 (1 day)
    Live Virtual | 11:00AM 7:00PM EDT
    Language English
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    Live Virtual |11:00AM 7:00PM EDT
    Live Virtual | 11:00AM 7:00PM EDT
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  • Apr 13, 2026 - Apr 13, 2026 (1 day)
    Live Virtual | 9:00AM 5:00PM EDT
    Language English
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    Live Virtual |9:00AM 5:00PM EDT
    Live Virtual | 9:00AM 5:00PM EDT
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  • May 15, 2026 - May 15, 2026 (1 day)
    Live Virtual | 9:00AM 5:00PM EDT
    Language English
    Select from 1 options below
    Live Virtual |9:00AM 5:00PM EDT
    Live Virtual | 9:00AM 5:00PM EDT
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  • Jun 15, 2026 - Jun 15, 2026 (1 day)
    Live Virtual | 9:00AM 5:00PM EDT
    Language English
    Select from 1 options below
    Live Virtual |9:00AM 5:00PM EDT
    Live Virtual | 9:00AM 5:00PM EDT
    Enroll
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FAQ

How do I get a Microsoft exam voucher?

Pearson Vue Exam vouchers can be requested and ordered with your course purchase or can be ordered separately by clicking here.

  • Vouchers are non-refundable and non-returnable. Vouchers expire 12 months from the date they are issued unless otherwise specified in the terms and conditions.
  • Voucher expiration dates cannot be extended. The exam must be taken by the expiration date printed on the voucher.

Do Microsoft courses come with post lab access?

Most Microsoft official courses will include post-lab access ranging from 30 to 180 calendar days after instructor led course delivery. A lab training key in class will be provided that can be leveraged to continue connecting to a remote lab environment for the individual course attendee.

Does the course schedule include a Lunchbreak?

Lunch is normally an hour-long after 3-3.5 hours of the class day.

What languages are used to deliver training?

Microsoft courses are conducted in English unless otherwise specified.

Reviews

It was very informative and covered all the required materials along with handson labs for practice.

ExitCertified gave a great course on AWS that covered all of the basics in depth with good lab materials.

I registered a day before class and am happy that I received all the materials and links in time for the class. Thanks.

I was very satisfied about how the course was organized. Sean Did a very good work

Class was very informative, although one lab didnt but will try again later

Objectives