Microsoft Fabric's perhaps least well-known area of functionality is its Data Science workload for AI. Unlike other parts of Fabric, which effectively integrate Azure technologies, Fabric's Data Science capabilities are not derived from Azure Machine Learning. Instead, Fabric embeds a variety of open source technologies, leverages the Apache Spark and notebook components used by Fabric's Data Engineering workload, and even has special semantic integrations with Power BI.

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 and this session is designed to get you up to speed. The session is presented by Andrew Brust, Microsoft Data Platform MVP, Fabric early adopter program participant, and a tech journalist and industry analyst focused on data and analytics.

You will learn:

• AutoML basics using FLAML, SynapseML and MLflow Tracking
• Use of Fabric's Data Wrangler and its Python code gen capabilities
• How to do Generative AI inferencing from Fabric notebooks