AI-103T00-A Develop AI Apps and Agents on Azure Certification Training

• Module 1: Develop Generative AI Apps in Azure
  • Plan and prepare to develop AI solutions on Azure
    • Introduction
    • What is AI?
    • Microsoft Foundry
    • Foundry Tools
    • Developer tools and SDKs
    • Responsible AI
    • Exercise – Prepare for an AI development project
  • Select, deploy, and evaluate Microsoft Foundry models
    • Introduction
    • Explore the model catalog
    • Select models using benchmarks
    • Deploy models to endpoints
    • Evaluate model performance
    • Exercise – Select, deploy, and evaluate models
  • Develop a generative AI chat app with Microsoft Foundry
    • Introduction
    • Explore with the model playground
    • Choose an endpoint and SDK
    • Generate responses with the Responses API
    • Generate responses with the ChatCompletions API
    • Exercise – Create a generative AI chat app
  • Develop generative AI apps that use tools
    • Introduction
    • What are tools?
    • Use the code_interpreter tool
    • Use the web_search tool
    • Use the file_search tool
    • Use the function tool
    • Exercise – Create a generative AI chat app that uses tools
  • Optimize generative AI model performance with Microsoft Foundry
    • Introduction
    • Optimize model output with prompt engineering
    • Ground your model with Retrieval Augmented Generation
    • Fine-tune a model for consistent behavior
    • Compare and combine optimization strategies
    • Exercise – Optimize generative AI model performance
  • Implement a responsible generative AI solution in Microsoft Foundry
    • Introduction
    • Plan a responsible generative AI solution
    • Map potential harms
    • Measure potential harms
    • Mitigate potential harms
    • Manage a responsible generative AI solution
    • Exercise – Apply guardrails to prevent the output of harmful content
• Module 2: Develop AI Agents on Azure
  • Develop AI agents with Microsoft Foundry and Visual Studio Code
    • Introduction
    • Understand AI agents and Microsoft Foundry Agent Service
    • Explore development approaches
    • Build your first agent in Microsoft Foundry
    • Set up Visual Studio Code for agent development
    • Configure and manage agents in Visual Studio Code
    • Extend agent capabilities with tools
    • Test, deploy, and integrate agents
    • Exercise – Build and deploy an AI agent
  • Integrate custom tools into your agent
    • Introduction
    • Why use custom tools
    • Options for implementing custom tools
    • How to integrate custom tools
    • Exercise – Build an agent with custom tools
  • Integrate MCP Tools with Azure AI Agents
    • Introduction
    • Understand the MCP tool discovery
    • Integrate agent tools using an MCP server and client
    • Use Azure AI agents with MCP servers
    • Exercise – Connect MCP tools to Azure AI Agents
  • Build knowledge-enhanced AI agents with Foundry IQ
    • Introduction
    • Understanding RAG for agents
    • Explore Foundry IQ
    • Configure data sources for knowledge bases
    • Configure retrieval with Foundry IQ
    • Exercise – Integrate an AI agent with Foundry IQ
  • Integrate your agent with Microsoft 365
    • Introduction
    • Understand Foundry agent publishing options
    • Publish an agent from the Foundry portal to Teams
    • Advanced – Use Microsoft 365 Agents Toolkit
    • Access Microsoft 365 data with Work IQ
    • Test and iterate your integrated agent
    • Exercise – Publish a Foundry agent to Teams
  • Build agent-driven workflows using Microsoft Foundry
    • Introduction
    • Understand Workflows
    • Identify Workflow Patterns
    • Create workflows in Microsoft Foundry
    • Add Agents to a Workflow
    • Apply Power Fx in Workflows
    • Maintain Workflows in Microsoft Foundry
    • Use workflows in code
    • Exercise – Create an Agent-driven Workflow
  • Develop an AI agent with Microsoft Agent Framework
    • Introduction
    • Understand Microsoft Agent Framework AI agents
    • Create an Azure AI agent with Microsoft Agent Framework
    • Add tools to the Azure AI agent
    • Exercise – Develop an Azure AI agent with the Microsoft Agent Framework SDK
  • Orchestrate a multi-agent solution using the Microsoft Agent Framework
    • Introduction
    • Understand the Microsoft Agent Framework
    • Understand agent orchestration
    • Use concurrent orchestration
    • Use sequential orchestration
    • Use group chat orchestration
    • Use handoff orchestration
    • Use Magnetic orchestration
    • Exercise – Develop a multi-agent solution
  • Discover Azure AI Agents with A2A
    • Introduction
    • Define an A2A agent
    • Implement an agent executor
    • Host an A2A server
    • Connect to your A2A agent
    • Exercise – Connect to remote Azure AI Agents with the A2A protocol
• Module 3: Develop Natural Language Solutions in Azure
  • Analyze text with Azure Language in Foundry Tools
    • Introduction
    • Azure Language in Microsoft Foundry Tools
    • Detect language
    • Extract entities
    • Extract personally identifiable information (PII)
    • Exercise – Analyze text
  • Develop a text analysis agent with the Azure Language MCP server
    • Introduction
    • Understand the Azure Language MCP server
    • Connect and use the Language MCP server with an agent
    • Exercise – Develop a text analysis agent
  • Develop a speech-capable generative AI application
    • Introduction
    • Choose a speech-capable model
    • Transcribe speech
    • Synthesize speech
    • Exercise – Use speech-capable generative AI models
  • Create speech-enabled apps with Azure Speech in Microsoft Foundry Tools
    • Introduction
    • Azure Speech in Foundry Tools
    • Use the Speech to Text API
    • Use the Text to Speech API
    • Configure audio format and voices
    • Use Speech Synthesis Markup Language
    • Exercise – Create a speech-enabled app
  • Develop a speech agent with the Azure Speech MCP server
    • Introduction
    • Understand the Azure Speech MCP server
    • Connect and use the Speech MCP server with an agent
    • Exercise – Use Azure Speech in an agent
  • Develop an Azure Speech Voice Live Agent in Microsoft Foundry
    • Introduction
    • Explore the Azure Voice Live API
    • Explore the AI Voice Live client library for Python
    • Create a Voice Live agent
    • Exercise – Develop a Voice Live agent
  • Translate text and speech with Microsoft Foundry Tools
    • Introduction
    • Translation in Microsoft Foundry
    • Translate text
    • Translate speech
    • Exercise – Translate text and speech
• Module 4: Extract Insights from Visual Data on Azure
  • Develop a vision-enabled generative AI application
    • Introduction
    • Use a vision-capable model in the Microsoft Foundry portal
    • Develop a vision-based chat app
    • Exercise – Develop a vision-enabled chat app
  • Generate images with AI
    • Introduction
    • What are image-generation models?
    • Explore image-generation models in the Microsoft Foundry portal
    • Create a client application that uses an image generation model
    • Exercise – Generate images with AI
  • Generate videos with Microsoft Foundry
    • Introduction
    • Deploy a video-generating model
    • Generate a video from a prompt
    • Generate video in Python
    • Exercise – Generate a video with Sora 2 in Microsoft Foundry
  • Analyze images with Content Understanding
    • Introduction
    • What is Content Understanding?
    • Analyze images with Content Understanding
    • Exercise – Analyze images with Content Understanding
  • Create a multimodal analysis solution with Azure Content Understanding
    • Introduction
    • What is Azure Content Understanding?
    • Create a Content Understanding analyzer
    • Use the Content Understanding API
    • Exercise – Extract information from multimodal content
  • Create an Azure Content Understanding client application
    • Introduction
    • Prepare to use the AI Content Understanding API
    • Create a Content Understanding analyzer
    • Analyze content
    • Exercise – Develop a Content Understanding client application
  • Extract data with Azure Document Intelligence
    • Introduction
    • What is Azure Document Intelligence?
    • Use the Document Intelligence Studio
    • Use prebuilt models
    • Train and use custom models
    • Exercise – Analyze documents with Document Intelligence
  • Create a knowledge mining solution with Azure AI Search
    • Introduction
    • What is Azure AI Search?
    • Extract data with an indexer
    • Enrich extracted data with AI skills
    • Search an index
    • Persist extracted information in a knowledge store
    • Exercise – Create a knowledge mining solution

• AI Developers
• Machine Learning Engineers
• Software Engineers
• Data Scientists
• AI Researchers
• Business Analysts
• Cloud Solution Architects
• Technical Consultants
• System Integrators
• IT Project Managers
• IT Operations Professionals
• Digital Transformation Specialists
• Technical Trainers in IT and AI fields
• Students pursuing careers in AI and Cloud Computing

• Basic knowledge of Microsoft Azure services
• Experience developing applications using Python
• Understanding of APIs and SDK-based application development
• Familiarity with general AI and generative AI concepts
• Basic knowledge of cloud computing and the software development lifecycle
• Exposure to data processing, search, or automation concepts is helpful but not mandatory

After completing this training, you will be able to:

• Plan, design, and manage Azure AI solutions using Microsoft Foundry.
• Select, deploy, and evaluate appropriate AI models for real-world business scenarios.
• Build generative AI applications using Foundry SDKs, APIs, endpoints, and model playgrounds.
• Implement Retrieval-Augmented Generation to ground AI responses in enterprise data.
• Develop AI agents that use tools, custom functions, knowledge sources, and workflows.
• Integrate custom tools, MCP tools, and Microsoft 365 capabilities into Azure AI agents.
• Orchestrate multi-agent solutions using Microsoft Agent Framework and agent workflow patterns.
• Create natural language solutions using Azure Language, Speech, and translation capabilities.
• Build vision-enabled and multimodal AI applications for image, video, and document analysis.
• Extract insights from structured and unstructured content using Azure Content Understanding, Document Intelligence, and Azure AI Search.