Please complete your modules and practice assessment as soon as possible. Vouchers are limited. 

Microsoft Certified Course

Azure AI Engineer Associate

Candidates for this Microsoft Certification should be adept at using generative AI productivity tools and core Microsoft 365 apps to enhance business outcomes and decision-making, without requiring coding or app development skills.

About the course

Azure AI Engineer Associate

Develop AI solutions in Azure is intended for software developers wanting to build AI infused applications that leverage Azure AI Foundry and other Azure AI services. Topics in this course include developing generative AI apps, building AI agents, and solutions that implement computer vision and information extraction. 

Finished the course?

Take the practice exam

Take the practice exam to test your knowledge and confirm your readiness for your certification. Passing the practice assessment with 70%+ is required before you can claim your free YES x Microsoft certification voucher.

Courses

You must complete every module within the below learning paths and pass the practice exam to qualify for the free certification voucher. Vouchers are limited so hurry and complete your courses within the next few days!

Develop generative AI apps in Azure

Plan and prepare to develop AI solutions on Azure

Microsoft Azure offers multiple services that enable developers to build amazing AI-powered solutions. Proper planning and preparation involves identifying the services you’ll use and creating an optimal working environment for your development team.

Choose and deploy models from the model catalog in Microsoft Foundry portal

Choose the various language models that are available through the Microsoft Foundry’s model catalog. Understand how to select, deploy, and test a model, and to improve its performance.

Develop an AI app with the Microsoft Foundry SDK

Use the Microsoft Foundry SDK to develop AI applications with Microsoft Foundry projects.

Get started with prompt flow to develop language model apps in the Microsoft Foundry

Learn about how to use prompt flow to develop applications that leverage language models in the Microsoft Foundry.

Develop a RAG-based solution with your own data using Microsoft Foundry

Retrieval Augmented Generation (RAG) is a common pattern used in generative AI solutions to ground prompts with your data. Microsoft Foundry provides support for adding data, creating indexes, and integrating them with generative AI models to help you build RAG-based solutions.

Fine-tune a language model with Microsoft Foundry

Train a base language model on a chat-completion task. The model catalog in Microsoft Foundry offers many open-source models that can be fine-tuned for your specific model behavior needs.

Implement a responsible generative AI solution in Microsoft Foundry

Generative AI enables amazing creative solutions, but must be implemented responsibly to minimize the risk of harmful content generation.

Evaluate generative AI performance in Microsoft Foundry portal

Evaluating copilots is essential to ensure your generative AI applications meet user needs, provide accurate responses, and continuously improve over time. Discover how to assess and optimize the performance of your generative AI applications using the tools and features available in the Azure AI Studio.

Get started with AI agent development on Azure

1AI agents represent the next generation of intelligent applications. Learn how they can be developed and used on Microsoft Azure.

Develop an AI agent with Microsoft Foundry Agent Service

This module provides engineers with the skills to begin building agents with Microsoft Foundry Agent Service.

Develop AI agents with the Microsoft Foundry extension in Visual Studio Code

Learn how to build, test, and deploy AI agents using the Microsoft Foundry extension in Visual Studio Code.

Integrate custom tools into your agent

Built-in tools are useful, but they may not meet all your needs. In this module, learn how to extend the capabilities of your agent by integrating custom tools for your agent to use.

Develop a multi-agent solution with Microsoft Foundry Agent Service

Break down complex tasks with intelligent collaboration. Learn how to design multi-agent solutions using connected agents.

Integrate MCP Tools with Azure AI Agents

Enable dynamic tool access for your Azure AI agents. Learn how to connect MCP-hosted tools and integrate them seamlessly into agent workflows.

Develop an AI agent with Microsoft Agent Framework

This module provides engineers with the skills to begin building Microsoft Foundry Agent Service agents with Microsoft Agent Framework.

Orchestrate a multi-agent solution using the Microsoft Agent Framework

Learn how to use the Microsoft Agent Framework SDK to develop your own AI agents that can collaborate for a multi-agent solution.

Discover Azure AI Agents with A2A

Learn how to implement the A2A protocol to enable agent discovery, direct communication, and coordinated task execution across remote agents.

Build agent-driven workflows using Microsoft Foundry

Workflows enable you to orchestrate AI agents and other components to create intelligent applications. Learn how to build and manage workflows using Microsoft Foundry.

Build knowledge-enhanced AI agents with Foundry IQ

Learn how to connect AI agents with enterprise knowledge using Foundry IQ. You’ll explore how Retrieval Augmented Generation (RAG) solves the knowledge problem for AI agents, discover how Foundry IQ provides a shared knowledge platform that multiple agents can access, improve retrieval quality through data optimization, and configure agent instructions for consistent, cited responses.

Analyze text with Azure Language

The Azure Language service enables you to create intelligent apps and services that extract semantic information from text.

Create question answering solutions with Azure Language

The question answering capability of the Azure Language service makes it easy to build applications in which users ask questions using natural language and receive appropriate answers.

Build a conversational language understanding model

The Azure Language conversational language understanding service (CLU) enables you to train a model that apps can use to extract meaning from natural language.

Create custom text classification solutions

The Azure Language service enables processing of natural language to use in your own app. Learn how to build a custom text classification project.

Custom named entity recognition

Build a custom entity recognition solution to extract entities from unstructured documents

Translate text with Azure Translator service

The Translator service enables you to create intelligent apps and services that can translate text between languages.

Create speech-enabled apps with Microsoft Foundry

The Azure Speech service enables you to build speech-enabled applications. This module focuses on using the speech-to-text and text to speech APIs, which enable you to create apps that are capable of speech recognition and speech synthesis

 

Translate speech with the Azure Speech service

Translation of speech builds on speech recognition by recognizing and transcribing spoken input in a specified language, and returning translations of the transcription in one or more other languages.

Develop an audio-enabled generative AI application

A voice carries meaning beyond words, and audio-enabled generative AI models can interpret spoken input to understand tone, intent, and language. Learn how to build audio-enabled chat apps that listen and respond to audio.

Develop an Azure AI Voice Live agent

Learn how to develop an Azure AI Voice Live agent using the Voice Live API and SDK. This module covers the fundamentals of the Voice Live platform, including API integration, SDK usage, and building conversational AI agents.

Analyze images

With the Azure Vision service, you can use pre-trained models to analyze images and extract insights and information from them.

Read text in images

The Azure Vision Image Analysis service uses algorithms to process images and return information. This module teaches you how to use the Image Analysis API for optical character recognition (OCR).

Detect, analyze, and recognize faces

The ability for applications to detect human faces, analyze facial features and emotions, and identify individuals is a key artificial intelligence capability.

Classify images

Image classification is used to determine the main subject of an image. You can use the Azure AI Custom Vision services to train a model that classifies images based on your own categorizations.

Detect objects in images

Object detection is used to locate and identify objects in images. You can use Azure AI Custom Vision to train a model to detect specific classes of object in images.

Analyze video

Azure Video Indexer is a service to extract insights from video, including face identification, text recognition, object labels, scene segmentations, and more.

Develop a vision-enabled generative AI application

A picture says a thousand words, and multimodal generative AI models can interpret images to respond to visual prompts. Learn how to build vision-enabled chat apps.

Generate images with AI

In Microsoft Foundry, you can use image generation models to create original images based on natural language prompts.

Create a multimodal analysis solution with Azure Content Understanding

Use Azure Content Understanding for multimodal content analysis and information extraction.

Create an Azure Content Understanding client application

Use the Azure Content Understanding REST API for multimodal content analysis and information extraction.

Use prebuilt Document intelligence models

Learn what data you can analyze by choosing prebuilt Forms Analyzer models and how to deploy these models in a Document intelligence solution.

Extract data from forms with Azure Document intelligence

Document intelligence uses machine learning technology to identify and extract key-value pairs and table data from form documents with accuracy, at scale. This module teaches you how to use the Azure Document intelligence cognitive service.

Create a knowledge mining solution with Azure AI Search

Unlock the hidden insights in your data with Azure AI Search. In this module, you’ll learn how to implement a knowledge mining solution that extracts and enriches data, making it searchable and ready for deeper analysis.

Finsihed the course?

Take the practice exam

Take the practice exam to test your knowledge and confirm your readiness for certification. Passing the practice assessment with 70%+ is required before you can claim your free YES x Microsoft certification voucher.

Finished your course and passed your practice exam? Claim your voucher!

If you have completed all required modules and passed your practice assessment, you qualify for a free certification voucher. Submit your voucher claim form to move forward with your final exam.