AI-3016: Develop custom copilots with Azure AI Studio

IT professionals, software developers, data engineers, solutions architects, data scientists, technology managers, and AI enthusiasts looking to learn how to develop custom virtual assistants using Azure AI Studio. These individuals are interested in integrating AI into their applications and systems to improve functionality, efficiency, and user experience in their respective fields.

Module 1 Introduction to Azure AI Foundry

• What is Azure Studio Artificial Intelligence?
• How Azure Studio AI Works
• Description of natural language processing
• When to use Azure Studio Artificial Intelligence
• Exercise: Explore Azure Studio Artificial Intelligence

Module 2: Browsing and deploying models from the Model Catalog in the Azure AI Foundry portal

• Browsing language models in the model catalog
• Deploying a model to an endpoint
• Improving the performance of a language model
• Exercise: Exploring, Implementing, and Chatting with Language Models

Module 3: Introduction to the prompt flow for developing language model applications in Azure Studio AI

• Description of the Large Language Model (LLM) Application Development Lifecycle
• Understanding the main components and exploring flow types
• Connection and runtime exploration
• Exploring variants and monitoring options
• Exercise: Introduction to the notification flow

Module 4: Building a RAG-based Copilot Solution with Your Own Data Using Azure Studio Artificial Intelligence

• Information on how to establish the language model
• Making data discoverable
• Creating a Copilot with a notification flow
• Exercise: Creating a custom copilot using your own data

Module 5: Tuning a Language Model with Azure AI Foundry

• Understanding when to optimize a language model
• Preparing data to optimize a chat completion model
• Exploring AI Optimization Language Models in Azure Studio
• Exercise: Adjusting a base model

Module 6: Evaluating the Performance of Generative AI Applications with Azure AI Foundry

• Model performance evaluation
• Manually Evaluating Model PerformanceEvaluating the Performance of Generative AI Applications
• Exercise: Evaluating the performance of the generative AI application

Module 7 Responsible generative artificial intelligence

• Planning a Responsible Generative AI Solution
• Identification of possible damage
• Measuring possible damage
• Mitigation of possible damages
• Operation of a responsible generative artificial intelligence solution
• Exercise: Exploring Content Filters in Azure Studio AI

Familiarity with Azure AI services and basic concepts is recommended.

• Course: English / Spanish
  

This course is part of the Microsoft Applied Skills Credentials.

Earn this Microsoft Applied Skills credential. In this course, you'll learn how to develop your own custom copilots using Azure AI Studio.

Applied Skills: Explore all credentials in one guide