What you'll learn

Many ML teams spend valuable time manually setting up experiments, tuning hyperparameters, and selecting models — work the platform can handle automatically.
In this course, Automate Machine Learning Using Databricks AutoML, you’ll gain the ability to design, run, and operationalize automated machine learning workflows in Databricks. First, you’ll explore the AutoML architecture, supported problem types, and how to configure Databricks Runtime for ML clusters. Next, you’ll discover how to launch and monitor experiments through the AutoML UI, register the best model in Unity Catalog, and understand deployment options. Finally, you’ll learn how to drive the full regression and classification workflow programmatically using the AutoML Python API, including generating predictions and exporting reproducible trial notebooks. When you’re finished with this course, you’ll have the skills and knowledge of Databricks AutoML needed to eliminate manual experimentation overhead and deliver production-ready models faster.