1 – Introduction to Azure AI Studio

• What is Azure AI Studio?
• How does Azure AI Studio work
• When to use Azure AI Studio

2 – Explore and deploy models from the model catalog in Azure AI Studio

• Explore the language models in the model catalog
• Deploy a model to an endpoint
• Improve the performance of a language model

3 – Get started with prompt flow to develop language model apps in the Azure AI Studio

• Understand the development lifecycle of a large language model (LLM) app
• Understand core components and explore flow types
• Explore connections and runtimes
• Explore variants and monitoring options

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

• Understand how to ground your language model
• Make your data searchable
• Build a copilot with prompt flow

5 – Integrate a fine-tuned language model with your copilot in the Azure AI Studio

• Understand when to fine-tune a language model
• Prepare your data to fine-tune a chat completion model
• Explore fine-tuning language models in Azure AI Studio

6 – Evaluate the performance of your custom copilot in the Azure AI Studio

• Assess the model performance
• Manually evaluate the performance of a model
• Assess the performance of your custom copilot

7 – Responsible generative AI in AI Studio

• Plan a responsible generative AI solution
• Identify potential harms
• Measure potential harms
• Mitigate potential harms
• Operate a responsible generative AI solution