AI-103T00: Develop AI Apps and Agents on Azure training course

1 – Plan and prepare to develop AI solutions on Azure

• What is AI?
• Microsoft Foundry
• Foundry Tools
• Developer tools and SDKs
• Responsible AI
• Module assessment

2 – Select, deploy, and evaluate Microsoft Foundry models

• Explore the model catalog
• Select models using benchmarks
• Deploy models to endpoints
• Evaluate model performance

3 – 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

4 – 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
• Module assessment

5 – 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
• Module assessment

6 – 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
• Module assessment

7 – 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

8 – Integrate custom tools into your agent

• Why use custom tools
• Options for implementing custom tools
• How to integrate custom tools
• Module assessment

9 – 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
• Module assessment

10 – 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

11 – Integrate your agent with Microsoft 365

• Understand Foundry agent publishing options
• Publish an agent from Foundry portal to Teams
• Advanced – Use Microsoft 365 Agents Toolkit
• Access Microsoft 365 data with Work IQ
• Test and iterate your integrated agent

12 – 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 in Microsoft Foundry
• Use workflows in code
• Module Assessment

13 – Develop an AI agent with Microsoft Agent Framework

• Understand Microsoft Agent Framework AI agents
• Create an Azure AI agent with Microsoft Agent Framework
• Add tools to Azure AI agent

14 – Orchestrate a multi-agent solution using the 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

15 – Discover Azure AI Agents with A2A

• Define an A2A agent
• Implement an agent executor
• Host an A2A server
• Connect to your A2A agent
• Module assessment

16 – Analyze text with Azure Language in Foundry Tools

• Azure Language in Microsoft Foundry Tools
• Detect language
• Extract entities
• Extract personally identifiable information (PII)
• Module assessment

17 – Develop a text analysis agent with the Azure Language MCP server

• Understand the Azure Language MCP server
• Connect and use the Language MCP server with an agent

18 – Develop a speech-capable generative AI application

• Choose a speech-capable model
• Transcribe speech
• Synthesize speech
• Module assessment

19 – Create speech-enabled apps with Azure Speech in Microsoft Foundry Tools

• 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
• Module assessment

20 – Develop a speech agent with the Azure Speech MCP server

• Understand the Azure Speech MCP server
• Connect and use the Speech MCP server with an agent

21 – Develop an Azure Speech Voice Live Agent in Microsoft Foundry

• Explore the Azure Voice Live API
• Explore the AI Voice Live client library for Python
• Create a Voice Live agent
• Module assessment

22 – Translate text and speech with Microsoft Foundry Tools

• Translation in Microsoft Foundry
• Translate text
• Translate speech
• Module assessment

23 – Develop a vision-enabled generative AI application

• Use a vision-capable model in the Microsoft Foundry portal
• Develop a vision-based chat app
• Module assessment

24 – Generate images with AI

• What are image-generation models?
• Explore image-generation models in Microsoft Foundry portal
• Create a client application that uses an image generation model
• Module assessment

25 – Generate videos with Microsoft Foundry

• Deploy a video generating model
• Generate video from a prompt
• Generate video in Python
• Module assessment

26 – Analyze images with Content Understanding

• What is Content Understanding?
• Analyze images with Content Understanding
• Module assessment

27 – Create a multimodal analysis solution with Azure Content Understanding

• What is Azure Content Understanding?
• Create a Content Understanding analyzer
• Use the Content Understanding API
• Module assessment

28 – Create an Azure Content Understanding client application

• Prepare to use the AI Content Understanding API
• Create a Content Understanding analyzer
• Analyze content
• Module assessment

29 – Extract data with Azure Document Intelligence

• What is Azure Document Intelligence?
• Use the Document Intelligence Studio
• Use prebuilt models
• Train and use custom models
• Module assessment

30 – Create a knowledge mining solution with Azure AI Search

• 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
• Module assessment