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.

This course covers the foundations of Generative AI, Generative-AI-Awareness and responsible AI-practices (including Terminology, Ethics and Biases).

Prerequisites

Before starting this module, you should be familiar with fundamental AI concepts and services in Azure. You should also have programming experience.

Course Modules

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.

• Introduction
• What is AI?
• Microsoft Foundry
• Foundry Tools
• Developer tools and SDKs
• Responsible AI
• Exercise - Prepare for an AI development project
• Module assessment
• Summary

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.

• Introduction
• Explore the model catalog
• Select models using benchmarks
• Deploy models to endpoints
• Evaluate model performance
• Exercise - Select, deploy, and evaluate models
• Knowledge check
• Summary

Develop a generative AI chat app with Microsoft Foundry

Use Microsoft Foundry to develop generative AI chat applications with projects and the Responses API.

• 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
• Knowledge check
• Summary

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.

• Introduction
• What are tools?
• Use the code_interpreter tool
• Use the web_search tool
• Use the file_search tool
• Use the functions tool
• Exercise - Create a generative AI chat app that uses tools
• Module assessment
• Summary

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.

• 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
• Module assessment
• Summary

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.

• 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 assessment
• Summary