AI-900: 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 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 AI Led training with interactive exercises using an active Azure subscription (provided as part of the course).

Category: AI and Machine Learning
Level: Foundational
Time Estimate: 10h 0m
Price: $99.99 for 3 months of access
Subscription: $39.99 per month after 7-day free trial
Lab Environment: Included
Free Trial: 7 Days

AI-900: Introduction to AI in Azure Badge

Lessons in this Course

Lesson 1: AI Overview

Lesson 1: AI Overview introduces the core concepts of Artificial Intelligence, including types of machine learning, common AI workloads, and the principles of responsible AI. Learners explore how Azure services such as Azure Machine Learning, Azure AI Services, and Azure Cognitive Search support AI development. The lesson concludes with hands-on labs to build a machine learning model using AutoML and explore Azure’s built-in AI services.

Duration: 2 h 0 m

Exercises

Exercise 1: AI Overview In this first lesson, we'll explore what artificial intelligence (AI) really is, how machine learning fits into AI, and how Microsoft Azure provides ready-to-use AI services. We'll wrap up with hands-on exercises to build and deploy AI solutions using Azure. Estimated Time: 45 minutes

Exercise 2: Explore Azure AI Services Azure AI services help users create AI applications with out-of-the-box and pre-built and customizable APIs and models. In this exercise you will create a resource in the Azure portal and try out Azure AI services. The goal of this exercise is to get a general sense of how Azure AI services are provisioned and used. Estimated Time: 45 minutes

Exercise 3: Explore Content Safety in Azure AI Foundry Azure AI services help users create AI applications with out-of-the-box and pre-built and customizable APIs and models. In this exercise you will take a look at one of the services, Azure AI Content Safety, which enables you to moderate text and image content. In Azure AI Foundry portal, Microsoft's platform for creating intelligent applications, you will use Azure AI Content Safety to categorize text and assign it severity score. Estimated Time: 45 minutes

Lesson 2: Computer Vision

Lesson 2: Computer Vision introduces the fundamentals of how AI interprets visual data through Azure AI Vision services. Learners explore capabilities such as image captioning, object detection, face recognition, and optical character recognition (OCR). Through practical exercises using Azure AI Foundry and Vision Studio, students learn to analyze images, detect faces, and extract text — equipping them to build vision-based AI solutions across industries like retail, healthcare, and manufacturing.

Duration: 2 h 0 m

Exercises

Exercise 1: Analyze images in Azure AI Foundry portal Azure AI Vision includes numerous capabilities for understanding image content and context and extracting information from images. In this exercise, you will use Azure AI Vision in Azure AI Foundry portal, Microsoft's platform for creating intelligent applications, to analyze images using the built-in try-it-out experiences. Suppose the fictitious retailer *Northwind Traders* has decided to implement a "smart store", in which AI services monitor the store to identify customers requiring assistance, and direct employees to help them. By using Azure AI Vision, images taken by cameras throughout the store can be analyzed to provide meaningful descriptions of what they depict. Estimated Time: 30 minutes

Exercise 2: Detect faces in Vision Studio Vision solutions often require AI to be able to detect human faces. Suppose the fictitious retail company Northwind Traders wants to locate where customers are standing in a store to best assist them. One way to accomplish this is to determine if there are any faces in the images, and if so, to return the bounding box coordinates that show their location. To test the face detection capabilities of the Azure AI Face service, you will use Vision Studio. This is a UI-based platform that lets you explore Azure AI Vision features without needing to write any code. Estimated Time: 45 minutes

Exercise 3: Read text in Vision Studio In this exercise you'll use Azure AI service to explore the optical character recognition capabilities of Azure AI Vision. You'll use Vision Studio to experiment with extracting text from images, without having to write any code. A common computer vision challenge is to detect and interpret text embedded within an image. This is known as optical character recognition (OCR). In this exercise youll use an Azure AI services resource, which includes Azure AI Vision services. You'll then use Vision Studio to try out OCR with different types of images. Estimated Time: 45 minutes

Lesson 3: Natural Language Processing

Lesson 3: Natural Language Processing introduces how AI can understand, analyze, and generate human language using Azure AI Language services. Learners explore key NLP tasks such as entity recognition, key phrase extraction, sentiment analysis, text summarization, and question answering. The lesson includes hands-on labs in Azure AI Foundry and Language Studio, helping students build solutions that can interpret language and respond intelligently

Duration: 2 h 0 m

Exercises

Exercise 1: Analyze text in Azure AI Foundry portal In this exercise, you will use Azure AI Language in Azure AI Foundry portal, Microsoft's platform for creating intelligent applications, to analyze hotel reviews. Estimated Time: 45 minutes

Exercise 2: Use Question Answering with the Language Studio In this exercise you will use Language Studio to create a knowledge base of question and answers. Content for the knowledge base will come from an existing FAQ page from the web site of Margie’s Travel, a fictitious travel agency. You will then use Language Studio to see how it would work when used by customers. Estimated Time: 45 minutes

Exercise 3: Use Conversational Language Understanding with Language Studio In this exercise, you will use Language Studio to create and test a project that sends instructions to devices such as lights or fans. You’ll use the capabilities of the Conversational Language Understanding service to configure your project. Estimated Time: 45 minutes

Exercise 4: Explore Speech in Azure AI Foundry portal In this exercise, you will use Azure AI Speech in Azure AI Foundry portal, Microsoft's platform for creating intelligent applications, to transcribe audio using the built-in try-it-out experiences. Estimated Time: 45 minutes

Lesson 4: Document Intelligence and Knowledge Mining

Lesson 4: Document Intelligence and Knowledge Mining explores how Azure AI can extract structured data from unstructured documents using Document Intelligence and enrich that data for powerful search scenarios using Azure AI Search. Learners use prebuilt models to analyze documents like receipts, and then build intelligent search indexes from customer data using enrichment skills like sentiment analysis and key phrase extraction. The lesson demonstrates how to transform content into searchable insights stored in a Knowledge Store.

Duration: 2 h 0 m

Exercises

Exercise 1: Extract data from documents in Azure AI Foundry portal In this exercise, you will use Azure AI Document Intelligence's prebuilt models in Azure AI Foundry portal, Microsoft's platform for creating intelligent applications, to recognize data from a receipt. Estimated Time: 45 minutes

Exercise 2: Explore an Azure AI Search index (UI) In this lab, you'll create Azure resources, extract and enrich data using AI skills, configure an indexer in the Azure portal, query a search index, and review results stored in a Knowledge Store. Estimated Time: 45 minutes

Lesson 5: Generative AI

Lesson 5: Generative AI introduces the fundamentals of generative artificial intelligence and the Azure OpenAI Service. Learners explore how models like GPT-4 can generate text, images, and code, and how to use these models responsibly. The lesson also covers deploying generative models in Azure AI Foundry, using playgrounds for experimentation, and applying content filters to ensure safe and ethical AI use.

Duration: 2 h 0 m

Exercises

Exercise 1: Explore generative AI in Azure AI Foundry Portal In this exercise, you try out generative AI in Azure AI Foundry portal, Microsoft's platform for creating intelligent applications. Estimated Time: 45 minutes

Exercise 2: Explore AI Studio In this exercise, you use Azure AI Foundry portal to create a hub and project, ready for a team of developers to build an AI solution. Estimated Time: 30 minutes

Exercise 3: Apply content filters to prevent the output of harmful content In this exercise, you'll explore the effect of the default content filters in Azure AI Foundry. Estimated Time: 30 minutes