- COURSE
Develop Copilots with Azure AI Studio (AI-3016)
Price:
Duration:
Generative Artificial Intelligence (AI) is becoming more accessible through easy-to-use platforms like Azure AI Studio. Learn how to build generative AI applications like custom copilots that use language models and prompt flow to provide value to your users.
This advanced course provides a comprehensive exploration of Azure AI Studio, emphasizing the development of AI copilots. Participants will learn to harness the power of Azure AI Studio to create, manage, and deploy language model applications. The course will cover core features, project management, prompt flow development, Retrieval Augmented Generation (RAG) for custom data integration, and responsible AI practices. Hands-on labs will reinforce theoretical knowledge through practical application.
Upcoming Class Dates and Times
All Sunset Learning courses are guaranteed to run
Course Outline and Details
Prerequisites
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#.
Target Audience
- Data Scientist
- AI Engineer
Course Objectives
- Plan and prepare to develop AI Solutions on Azure
- Choose and deploy models from the model catalog in Azure AI Foundry portal
- Develop an AI app with the Azure AI Foundry SDK
- Get started with prompt flow to develop language model apps in the Azure AI Foundry
- Develop a RAG-based solution with your own data using Azure AI Foundry
- Fine-tune a language model with Azure AI Foundry
- Implement a responsible generative AI solution in Azure AI Foundry
- Evaluate generative AI performance in Azure AI Foundry portal
Course Outline
Plan and prepare to develop AI Solutions on Azure
- What is AI?
- Azure AI services
- Azure AI Foundry
- Developer tools and SDK's
- 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 & chat with language models
Develop an AI app with the Azure AI Foundry SDK
- What is the Azure AI Foundry SGK?
- 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 Studio
- 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