Develop custom copilots with Azure AI Studio (AI-3016) [M-AI3016]

OVERVIEW

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.

CONTENT

Module 1 : Introduction to Azure AI Studio

Microsoft Azure offers multiple services that enable developers to build amazing AI-powered solutions. Azure AI Studio brings these services together in a single unified experience for AI development on the Azure cloud platform.

By the end of this module 1, you'll be able to:

• Describe core features and capabilities of Azure AI Studio
• Use Azure AI Studio to provision and manage an Azure AI resource
• Use Azure AI Studio to create and manage an AI project
• Understand when to use Azure AI Studio

Module 2 : Get started with prompt flow to develop language model apps in the Azure AI Studio

Learn about how to use prompt flow to develop applications that leverage language models in the Azure AI Studio.

By the end of this module 2 , you'll be able to:

• 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.

Module 3 : Build a RAG-based copilot solution with your own data using Azure AI Studio

Copilots can work alongside you to provide suggestions, generate content, or help you make decisions. Copilots use language models as a form of generative artificial intelligence (AI) and will answer your questions using the data they were trained on. To ensure a copilot retrieves information from a specific source, you can add your own data when building a copilot with the Azure AI Studio.

By the end of this module 3 , you'll be able to:

• Identify the need to ground your language model with Retrieval Augmented Generation (RAG)
• Index your data with Azure AI Search to make it searchable for language models
• Build a copilot using RAG on your own data in the Azure AI Studio

Module 4 : Responsible generative AI in AI Studio

Generative AI enables amazing creative solutions, but must be implemented responsibly to minimize the risk of harmful content generation.

By the end of this module 4 , you'll be able to:

• Describe an overall process for responsible generative AI solution development
• Identify and prioritize potential harms relevant to a generative AI solution
• Measure the presence of harms in a generative AI solution
• Mitigate harms in a generative AI solution
• Prepare to deploy and operate a generative AI solution responsibly