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AI-3016 Develop copilots with Azure AI Studio
Those who want to build AI assistants – not just use them – are in the right place. Azure AI Studio gives you the tools to turn ideas into real copilot solutions: structured, scalable and ready to deploy.
Key topics
- Building intelligent copilots with Azure AI Studio – from configuration to deployment.
- Designing prompt structures and steering large language models effectively.
- Integrating data sources, APIs and business logic into copilot solutions.
- Applying security policies, governance requirements and responsible AI practices.
- Testing, optimising and operating copilot solutions in production.
Prerequisite
A basic understanding of cloud or Azure services is helpful, as is some practical experience in AI or software development.
Target group
Developers, IT architects and technically oriented professionals who want to independently design and implement AI-powered assistants.
You will gain the knowledge to not only understand copilots, but to integrate them productively into existing system landscapes – securely, maintainably and ready for the future.
course content
Getting familiar with Azure AI Studio
- Explore the core features and capabilities of Azure AI Studio.
- Provision and manage an Azure AI resource using Azure AI Studio.
- Create and manage an AI project within Azure AI Studio.
- Identify the right situations to use Azure AI Studio.
Developing language model apps with Prompt Flow
- Understand the end-to-end development cycle for language model applications.
- Describe what a flow in Prompt Flow is and how it works.
- Examine and apply the core components when working with Prompt Flow.
Building a RAG-based copilot with your own data
- Recognise why grounding a language model with Retrieval Augmented Generation (RAG) is necessary for reliable outputs.
- Index your own data with Azure AI Search to make it searchable for language models.
- Build a copilot in Azure AI Studio that draws on your own data using RAG.
Developing and deploying generative AI responsibly
- Describe an end-to-end process for developing generative AI solutions responsibly.
- Identify and prioritise potential harms relevant to a generative AI solution.
- Measure and evaluate the presence of harms in a generative AI solution.
- Mitigate identified harms effectively.
- Prepare for the responsible deployment and ongoing operation of a generative AI solution.
