Building End-to-End ML Systems With Genie Code

Coding agents are transforming how data science teams build and operate machine learning systems. In this session, we'll explore how teams use Genie Code across the ML lifecycle—across EDA, feature engineering, model development, evaluation, deployment, and monitoring.

We'll also provide an inside look at how Genie Code was built and optimized for ML workflows. Genie Code understands your data through Unity Catalog and leverages metadata, business semantics, governance policies, and lineage to provide context-aware assistance. Deep integration across the Databricks ML stack enables teams to move faster and work with greater confidence.

We'll then look ahead at how Genie Code is evolving from a coding assistant into an agent that can help deploy, serve, and operate ML systems in production. You'll also learn how to customize Genie Code for your ML team through skills and instructions, as well as other tips and tricks to get the most out of Genie Code.

Attendees will leave with practical examples of how coding agents are reshaping machine learning and actionable guidance for applying these capabilities to their own ML projects.