Microsoft Fabric's perhaps least well-known area of functionality is its Data Science workload for AI. Rather than using Azure Machine Learning, Fabric embeds a variety of open-source technologies, leverages the Apache Spark and notebook components used by Fabric's Data Engineering workload. For generative AI, there are code-first techniques, a Data Science Copilot, and "AI skills," a natural language query technology for data warehouses and data lakes.

As a modern data stack professional or data scientist, you can get a ton of value from Fabric Data Science, but you have to know how to use it. This session is designed to get you up to speed, on the relevant Fabric components _and_ the AI concepts underlying them.

You will learn:

• Leveraging Fabric's generative AI features including Data Science Copilot and AI skills
• AutoML basics using FLAML, SynapseML and MLflow Tracking
• Use of Fabric's Data Wrangler and its Python code gen capabilities