Copilot

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 copilots that can assist humans in creative tasks.


By the end of this module, you are able to:
Understand generative AI's place in the development of artificial intelligence.
Understand language models and their role in intelligent applications.
Describe examples of copilots and good prompts.

Introduction

What is generative AI?

What are language models?

Using language models

What are copilots?

Microsoft Copilot

Considerations for Copilot prompts

Extending and developing copilots

Exercise - Explore Microsoft Copilot

Fundamentals of Generative AI

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.

This module explains how to:
Create agents.
Test agents.
Analyze performance.

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

Get started with Microsoft Copilot 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, 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


What is Azure AI Studio?

How does Azure AI Studio work

When to use Azure AI Studio

Exercise - Explore Azure AI Studio

Introduction to 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, 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


Understand how to ground your language model

Make your data searchable

Build a copilot with prompt flow

Exercise - Create a custom copilot that uses your own data

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

Copilot Foundations introduces participants to the basics of generative AI and language models, focusing on creating, testing, and managing intelligent AI copilots. Through hands-on labs using Microsoft Copilot and Azure AI Studio, learners will explore effective prompting techniques, develop custom copilot solutions using Retrieval Augmented Generation (RAG) with their own data, and gain practical experience in managing AI projects and resources.

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.