Develop generative AI apps in Azure

After completing this course, students will be able to: Select a language model from the model catalog Deploy a model to an endpoint Test a model and improve the performance of the model Describe capabilities of the Azure AI Foundry SDK Use the Azure AI Foundry SDK to work with connections in projects Use the Azure AI Foundry SDK to develop an AI chat app Understand the development lifecycle when creating language model applications Understand what a flow is in prompt flow Explore the core components when working with prompt flow Prepare your data to fine-tune a chat completion model Fine-tune a base model in the Azure AI Foundry portal
 

Data Scientist, AI Engineer
 

• Before starting this module, you should be familiar with fundamental AI concepts and services in Azure. You should also be proficient in programming with Python or Microsoft C#.

Plan and prepare to develop AI solutions on Azure

• Introduction
• What is AI?
• Azure AI services
• Azure AI Foundry
• Developer tools and SDKs
• Responsible AI
• Exercise - Explore the Azure AI Foundry portal
• Module assessment

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

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

Develop an AI app with the Azure AI Foundry SDK

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

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

• Introduction
• 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
• Module assessment

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

• Introduction
• 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
• Module assessment

Fine-tune a language model with Azure AI Foundry

• Introduction
• 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 Studio
• Exercise - Fine-tune a foundation model
• Module assessment

Implement a responsible generative AI solution in Azure AI Foundry

• Introduction
• 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
• Module assessment

Evaluate generative AI performance in Azure AI Foundry portal

• Introduction
• Assess the model performance
• Manually evaluate the performance of a model
• Automated evaluations
• Exercise - Evaluate generative AI model performance
• Module assessment