Develop generative AI apps in Azure

• Plan and prepare to develop AI solutions on Azure
  • 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
  • Explore the model catalog
  • Select models using benchmarks
  • Deploy models to endpoints
  • Evaluate model performance
• Develop a generative AI chat app with Microsoft Foundry
  • Explore with the model playground
  • Choose an endpoint and SDK
  • Generate responses with the Responses API
  • Generate responses with the ChatCompletions API
• Develop generative AI apps that use tools
  • What are tools?
  • Use the code_interpreter tool
  • Use the web_search tool
  • Use the file_search tool
  • Use the functions tool
• Optimize generative AI model performance with Microsoft Foundry
  • 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
• Implement a responsible generative AI solution in Microsoft Foundry
  • Plan a responsible generative AI solution
  • Map potential harms
  • Measure potential harms
  • Mitigate potential harms
  • Manage a responsible generative AI solution

Develop AI agents on Azure

• Develop AI agents with Microsoft Foundry and Visual Studio Code
  • 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
• Integrate custom tools into your agent
  • Why use custom tools
  • Options for implementing custom tools
  • How to integrate custom tools
• Integrate MCP Tools with Azure AI Agents
  • Understand MCP tool discovery
  • Integrate agent tools using an MCP server and client
  • Use Azure AI agents with MCP servers
• Build knowledge-enhanced AI agents with Foundry IQ
  • Understanding RAG for agents
  • Explore Foundry IQ
  • Configure data sources for knowledge bases
  • Configure retrieval with Foundry IQ
• Integrate your agent with Microsoft 365
  • Understand Foundry agent publishing options
  • Publish an agent to Teams
  • Use Microsoft 365 Agents Toolkit
  • Access Microsoft 365 data with Work IQ
  • Test and iterate your integrated agent
• Build agent-driven workflows using Microsoft Foundry
  • Understand workflows
  • Identify workflow patterns
  • Create workflows in Microsoft Foundry
  • Add agents to a workflow
  • Apply Power Fx in workflows
  • Maintain workflows
  • Use workflows in code
• Develop an AI agent with Microsoft Agent Framework
  • Understand Microsoft Agent Framework AI agents
  • Create an Azure AI agent
  • Add tools to Azure AI agent
• Orchestrate a multi-agent solution using Microsoft Agent Framework
  • Understand the Microsoft Agent Framework
  • Understand agent orchestration
  • Use concurrent orchestration
  • Use sequential orchestration
  • Use group chat orchestration
  • Use handoff orchestration
  • Use Magentic orchestration
• Discover Azure AI Agents with A2A
  • Introduction
  • Define an A2A agent
  • Implement an agent executor
  • Host an A2A server
  • Connect to your A2A agent

Develop natural language solutions in Azure

• Analyze text with Azure Language
  • Azure Language in Foundry Tools
  • Detect language
  • Extract entities
  • Extract personally identifiable information (PII)
• Develop a text analysis agent
  • Understand the Azure Language MCP server
  • Connect and use the Language MCP server
• Develop a speech-capable generative AI application
  • Choose a speech-capable model
  • Transcribe speech
  • Synthesize speech
• Create speech-enabled apps
  • 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
• Develop a speech agent
  • Understand the Azure Speech MCP server
  • Connect and use the Speech MCP server
  • Exercise - Use Azure Speech in an agent
• Develop an Azure Speech Voice Live Agent
  • Introduction
  • Explore the Azure Voice Live API
  • Explore the AI Voice Live client library
  • Create a Voice Live agent
• Translate text and speech
  • Introduction
  • Translation in Microsoft Foundry
  • Translate text
  • Translate speech

Extract insights from visual data on Azure

• Develop a vision-enabled generative AI application
  • Use a vision-capable model
  • Develop a vision-based chat app
• Generate images with AI
  • What are image-generation models?
  • Explore image-generation models
  • Create a client application
• Generate videos with Microsoft Foundry
  • Deploy a video generating model
  • Generate video from a prompt
  • Generate video in Python
• Analyze images with Content Understanding
  • What is Content Understanding?
  • Analyze images
• Create a multimodal analysis solution
  • What is Azure Content Understanding?
  • Create a Content Understanding analyzer
  • Use the Content Understanding API
• Create a Content Understanding client application
  • Prepare to use the API
  • Create a Content Understanding analyzer
  • Analyze content
• Extract data with Azure Document Intelligence
  • What is Azure Document Intelligence?
  • Use the Document Intelligence Studio
  • Use prebuilt models
  • Train and use custom models
• Create a knowledge mining solution with Azure AI Search
  • What is Azure AI Search?
  • Extract data with an indexer
  • Enrich data with AI skills
  • Search an index
  • Persist data in a knowledge store