Develop Generative AI Apps in Azure (AI-3016)

Generative Artificial Intelligence (AI) is becoming more accessible through comprehensive development platforms like Azure AI Foundry. Learn how to build generative AI applications that use language models to chat with your users.

Develop Generative AI Apps in Azure (AI-3016) Benefits

• In this course, you will:

  • Engage in practical exercises to build custom copilots and develop language model applications.
  • Understand the full lifecycle of AI development, from conceptualization to implementation.
  • Learn how to implement generative AI responsibly, ensuring ethical considerations and minimizing risks.
  • Gain skills to create tailored AI solutions using your own data, enhancing the relevance and effectiveness of AI applications.

• Training Prerequisites

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

Develop generative AI apps in Azure Training Outline

Learning Objectives

Plan and prepare to develop AI solutions on Azure

• What is AI?
• Azure AI services
• Azure AI Foundry
• Developer tools and SDKs
• Responsible AI
• Exercise – Prepare for an AI development project

Choose and deploy models from the model catalog in Azure AI Foundry portal

• Explore the model catalog
• Deploy a model to an endpoint
• Optimize model performance
• Exercise – Explore, deploy, and chat with language models

Develop an AI app with the Azure AI Foundry SDK

• What is the Azure AI Foundry SDK?
• Work with project connections
• Create a chat client
• Exercise – Create a generative AI chat app

Get started with prompt flow to develop language model apps in the Azure AI Foundry

• Understand the development lifecycle of a large language model (LLM) app
• Understand core components and explore flow types
• Explore connections and runtimes
• Explore variants and monitoring options
• Exercise – Get started with prompt flow

Develop a RAG-based solution with your own data using Azure AI Foundry

• Understand how to ground your language model
• Make your data searchable
• Create a RAG-based client application
• Implement RAG in a prompt flow
• Exercise – Create a generative AI app that uses your own data

Fine-tune a language model with Azure AI Foundry

• Understand when to fine-tune a language model
• Prepare your data to fine-tune a chat completion model
• Explore fine-tuning language models in Azure AI Foundry portal
• Exercise – Fine-tune a language model

Implement a responsible generative AI solution in Azure AI Foundry

• Plan a responsible generative AI solution
• Map potential harms
• Measure potential harms
• Mitigate potential harms
• Manage a responsible generative AI solution
• Exercise – Apply content filters to prevent the output of harmful content

Evaluate generative AI performance in Azure AI Foundry portal

• Assess the model performance
• Manually evaluate the performance of a model
• Automated evaluations
• Exercise – Evaluate generative AI model performance