Copilots are quickly becoming a popular way to use with AI models, automate tasks, and improve productivity. In this learning path, you'll explore options for adopting, using, and creating copilots.

Prerequisites

Familiarity with Azure and the Azure portal.

Modules in this learning path

Fundamentals of Generative AI

In this module, you explore the way in which language models enable AI applications and services to generate original content based on natural language input. You also learn how generative AI enables the creation of agents that can assist humans in creative tasks.

• Introduction
• What is generative AI?
• What are language models?
• Using language models
• Understand agents
• Understand Microsoft Copilot
• Considerations for prompts
• Extending and developing copilot-like agents
• Exercise - Explore Microsoft Copilot
• Knowledge check
• Summary

Get started with Microsoft Copilot Studio

Microsoft Copilot Studio allows organizations to quickly create agents based on business scenarios their customers and employees can easily interact with as needed. In this module, you're introduced to key concepts for agents.

• Introduction
• Get started working with environments
• Create agents and work with the Microsoft Copilot Studio interface
• Create topics
• Enhancing productivity with Generative AI
• Test your agents
• Publish agents and analyze performance
• Exercise - Create an agent with Microsoft Copilot Studio
• Check your knowledge
• Summary

Introduction to Azure AI Foundry

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

• Introduction
• What is Azure AI Foundry?
• How does Azure AI Foundry work
• When to use Azure AI Foundry
• Exercise - Explore the Azure AI Foundry portal
• Knowledge check
• Summary

Build a RAG-based agent with your own data using Azure AI Foundry

Agents can work alongside you to provide suggestions, generate content, or help you make decisions. Agents 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 an agent retrieves information from a specific source, you can add your own data when building an agent with the Azure AI Foundry.

• Introduction
• Understand how to ground your language model
• Make your data searchable
• Build an agent with prompt flow
• Exercise - Create a custom agent that uses your own data
• Knowledge check
• Summary