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AI-103T00: Develop AI App and Agents on Azure

By Tyler Farmer
4 Days
Live Class Recording
April 27, 2026
Course Description

 

What you will learn

With a focus on practical applications, the course covers:

  • Generative AI Development
  • Agentic AI & Orchestration
  • Retrieval-Augmented Generation (RAG
  • Azure AI Foundry
  • Multimodal Capabilities
  • Security & Governance

What products and services will you use and learn about in this course 

Generative AI and Agentic Solutions

  • Azure OpenAI
  • Prompt Engineering
  • RAG (Retrieval-Augmented Generation
  • AI Agents

Computer Vision Solutions

  • Image Analysis
  • Custom Vision
  • Video Analysis
  • OCR

Natural Language Processing (NLP) and Speech

  • Language Analysis
  • Conversational AI
  • Speech Services

Knowledge Mining and Information Extraction

  • Azure AI Search
  • Document Intelligence

Responsible AI and Security

  • Content Safety
  • Security
  • Monitoring

Prepare for the Microsoft Certified: Azure AI Apps and Agents Developer Associate (beta)

This course is designed to help students confidently prepare for the AI-103: Microsoft Certified: Azure AI Apps and Agents Developer Associate (beta) exam. This exam is expected to go live in June 2026. The study areas for the certification exam related to this course are based on the Job Task Analysis (JTA) that was conducted in March 2026.

Note: To pass the certification test, studying outside the course may be required to ensure all the concepts are fully understood.

Course Outline

Module 1: Develop generative AI apps in Azure

Generative artificial intelligence (AI) is becoming more accessible through comprehensive development platforms like Microsoft Foundry. Learn how to build generative AI applications that use language models to interact with your users.

Lessons:

  • Plan and prepare to develop AI solutions on Azure
  • Select, deploy, and evaluate Microsoft Foundry models
  • Develop a generative AI chat app with Microsoft Foundry
  • Develop generative AI apps that use tools
  • Optimize generative AI model performance with Microsoft Foundry
  • Implement a responsible generative AI solution in Microsoft Foundry

Exercises:

  • Prepare for an AI development project
  • Select, deploy, and evaluate models
  • Create a generative AI chat app
  • Create a generative AI chat app that uses tools
  • Optimize generative AI model performance
  • Apply guardrails to prevent the output of harmful content

Module 2: Develop AI agents on Azure

Generative Artificial Intelligence (AI) is becoming more functional and accessible, and AI agents are a key component of this evolution. This learning path will help you understand the AI agents, including when to use them and how to build them, using Microsoft Foundry Agent Service and Microsoft Agent Framework. By the end of this learning path, you will have the skills needed to develop AI agents on Azure.

Lessons:

  • Develop AI agents with Microsoft Foundry and Visual Studio Code
  • Integrate custom tools into your agent
  • Integrate MCP Tools with Azure AI Agents
  • Build knowledge-enhanced AI agents with Foundry IQ
  • Integrate your agent with Microsoft 365
  • Build agent-driven workflows using Microsoft Foundry
  • Develop an AI agent with Microsoft Agent Framework
  • Orchestrate a multi-agent solution using the Microsoft Agent Framework
  • Discover Azure AI Agents with A2A

Exercises:

  • Build and deploy an AI agent
  • Build an agent with custom tools
  • Connect MCP tools to Azure AI Agents
  • Integrate an AI agent with Foundry IQ
  • Publish a Foundry agent to Teams
  • Create an Agent-driven Workflow
  • Develop an Azure AI agent with the Microsoft Agent Framework SDK
  • Develop a multi-agent solution
  • Connect to remote Azure AI Agents with the A2A protocol

Module 3: Develop natural language solutions in Azure

Natural language solutions use language models to interpret the semantic meaning of written or spoken language, and in some cases respond based on that meaning. You can use Microsoft Foundry to develop AI apps and agents that can analyze text, transcribe and synthesize speech, and translate languages.

Lessons:

  • Analyze text with Azure Language in Foundry Tools
  • Develop a text analysis agent with the Azure Language MCP server
  • Develop a speech-capable generative AI application
  • Create speech-enabled apps with Azure Speech in Microsoft Foundry Tools
  • Develop a speech agent with the Azure Speech MCP server
  • Develop an Azure Speech Voice Live Agent in Microsoft Foundry
  • Translate text and speech with Microsoft Foundry Tools

Exercise:

  • Analyze text
  • Develop a text analysis agent
  • Use speech-capable generative AI models
  • Create a speech-enabled app
  • Use Azure Speech in an agent
  • Develop a Voice Live agent
  • Translate text and speech

Module 4: Extract insights from visual data on Azure

Use generative AI, computer vision, and Content Understanding capabilities in Azure to extract insights from visual data, supporting scenarios like:

  • Image analysis
  • Image and video generation
  • Content Understanding and enrichment
  • Visual search and classification
  • Digital asset management (DAM)
  • Multimodal AI solutions

Lessons:

  • Develop a vision-enabled generative AI application
  • Generate images with AI
  • Generate videos with Microsoft Foundry
  • Analyze images with Content Understanding
  • Create a multimodal analysis solution with Azure Content Understanding
  • Create an Azure Content Understanding client application
  • Extract data with Azure Document Intelligence
  • Create a knowledge mining solution with Azure AI Search

Exercise:

  • Develop a vision-enabled chat app
  • Generate images with AI
  • Generate video with Sora 2 in Microsoft Foundry
  • Analyze images with Content Understanding
  • Extract information from multimodal content
  • Develop a Content Understanding client application
  • Analyze documents with Document Intelligence
  • Create a knowledge mining solution
Course Content
Course Introduction
Course Introduction
Overview of Machine Learning and History of AI
Overview of Machine Learning and History of AI
Develop Generative AI Apps in Azure
Overview of Azure
Plan and Prepare to Develop AI Solutions on Azure
Demo of the Lab Environment and Lab 1
Select, Deploy, and Evaluate Foundry Models
Develop a Generative AI Chat App
Continuation of Lunch and Lab Time
Develop Generative AI Apps that use Tools
Optimize Generative AI Model Performance
Implement a Responsible Generative AI Solution
Developing Azure AI Apps and Agents
Different type of Agents
Develop AI Agents with Foundry and VS Code
Demo - Using the Code Interpreter Tool
Integrate Custom Tools into your Agent
Integrate MCP Tools with Azure AI Agents
Build Knowledge-Enhanced AI Agents with Foundry IQ
Build Knowledge-Enhanced AI Agents with Foundry IQ (continued)
Integrate your Agent with M365
Build Agent-driven Workflows using Microsoft Foundry
Develop an AI Agent with Microsoft Agent Framework
Orchestrate a Multi-Agent Solution using the Agent Framework
A2A Protocol
Developing Natural Language Solutions in Azure
Analyze Text with Azure Language in Foundry Tools
Develop a Text Analysis Agent with Azure Language MCP Server
Develop a Speech-capable Generative AI App
Create Speech-Enabled Apps
Develop a Speech Agent with Azure Speech MCP Server
Develop an Azure Speech Voice Live Agent
Translate Text and Speech with Foundry Tools
Demo of Video Avatars
Continuation of Lab Time
Extract Insights from Visual Data in Azure
Develop a Vision-Enabled Generative AI App
Generating Images and Video
Side Topic: Costs of using AI
Side Topic: Costs of using AI
Extract Insights from Visual Data in Azure
Analyze Images with Content Understanding
Analyze Documents with Content Understanding
Course Handouts
Course Handouts
Extract Insights from Visual Data in Azure
Content Understanding API