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.
- Developers building generative AI applications on Azure
- AI Engineers and Data Scientists working with Microsoft Foundry
- Solution Architects planning generative AI solutions for their organization
- Individuals who have completed foundational AI training and are familiar with core Azure AI concepts and services
By the end of the course, participants should be able to:
- Plan and prepare an Azure environment for generative AI development using Microsoft Foundry.
- Select, deploy, and evaluate language models from the Foundry model catalog.
- Build generative AI chat applications using Foundry projects and the Responses API.
- Extend generative AI apps with tools such as code interpreters, web search, file search, and custom functions.
- Optimize model performance through prompt engineering, retrieval-augmented generation, and fine-tuning.
- Implement responsible AI practices to identify, measure, and mitigate potential harms.
Module 01: 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.
Topics
- What is AI?
- Microsoft Foundry
- Foundry Tools
- Developer tools and SDKs
- Responsible AI
- Exercise - Prepare for an AI development project
Module 02: Select, deploy, and evaluate Microsoft Foundry models
Explore how to select appropriate models from the model catalog using benchmarks, deploy them to endpoints, and evaluate their performance using manual and automated approaches in Microsoft Foundry portal.
Topics
- Explore the model catalog
- Select models using benchmarks
- Deploy models to endpoints
- Evaluate model performance
- Exercise - Select, deploy, and evaluate models
Module 03: Develop a generative AI chat app with Microsoft Foundry
Use Microsoft Foundry to develop generative AI chat applications with projects and the Responses API.
Topics
- 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
Module 04: Develop generative AI apps that use tools
Tools enable models to perform tasks and interact with external systems, enabling them to extend their capabilities beyond basic chat interactions.
Topics
- 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
Module 05: Optimize generative AI model performance with Microsoft Foundry
Explore complementary strategies to optimize generative AI model performance. Learn how to apply prompt engineering, ground your model with RAG, and fine-tune for consistent behavior—and when to combine these approaches.
Topics
- 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
Module 06: 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.
Topics
- 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
