- Home
- IT Courses
- MS-AI3018: Copilot Foundations
MS-AI3018: Copilot Foundations
Course Code: MS-AI3018
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.
This course is designed for a range of professionals interested in advancing their skills in generative AI and AI project management. The primary audience includes:
- AI Enthusiasts: Individuals keen on exploring the fundamentals and applications of generative AI.
- Data Scientists: Professionals looking to enhance their expertise in AI and machine learning.
- IT Professionals: Those involved in developing or managing AI-driven solutions.
- Business Analysts and Technical Leads: Individuals responsible for overseeing AI projects and integrating AI solutions into business processes.
Familiarity with Azure and the Azure portal..
After attending this course, delegates will be able to:
- Grasp the fundamentals of generative AI and its role in AI development.
- Get started with Microsoft Copilot Studio.
- Introduction to Azure AI Studio and its core features.
- Develop custom copilot solutions using Retrieval Augmented Generation (RAG) with your own data.
There is no Associated Certification or Exam for this course.
Modules
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.
Lessons
- 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.
- Knowledge check.
- Summary.
By the end of this module, you’ll be 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.
Microsoft Copilot Studio allows organizations to quickly create copilots based on business scenarios their customers and employees can easily interact with as needed. In this module, you're introduced to key concepts for copilots.
Lessons
- Introduction.
- Get started working with environments.
- Create copilots and work with the Microsoft Copilot Studio interface.
- Enhancing productivity with Generative AI.
- Create topics.
- Test bots.
- Publish bots and analyse performance.
- Exercise - Microsoft Copilot Studio.
- Check your knowledge.
- Summary.
By the end of this module, you’ll be able to:
- Create copilots.
- Test copilots.
- Analyze performance.
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.
Lessons
- Introduction.
- What is Azure AI Studio?
- How does Azure AI Studio work.
- When to use Azure AI Studio.
- Exercise - Explore Azure AI Studio.
- Knowledge check.
- Summary.
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
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.
Lessons
- Introduction.
- 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
- Knowledge check
- Summary.
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