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