Develop your own custom copilots with Azure AI Studio
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.
Prerequisites
Before starting this module, you should be familiar with fundamental AI concepts and services in Azure. Consider completing the Get started with artificial intelligence learning path first.
Achievement Code
Would you like to request an achievement code?
Modules in this learning path
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.
Explore the various language models that are available through the Azure AI Studio's model catalog. Understand how to select, deploy, and test a model, and to improve its performance.
Learn about how to use prompt flow to develop applications that leverage language models in the 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.
Train a base language model on a chat-completion task. The model catalog in the Azure AI Studio offers many open-source models that can be fine-tuned for your specific model behavior needs.
Evaluating copilots is essential to ensure your custom copilots meet user needs, provide accurate responses, and continuously improve over time. Discover how to assess and optimize the performance of your custom copilot using the tools and features available in the Azure AI Studio.
Generative AI enables amazing creative solutions, but must be implemented responsibly to minimize the risk of harmful content generation.