The Databricks Lakehouse unifies data warehousing and data lakes on open formats, so the same governed tables feed both analytics and machine learning. Databricks Machine Learning is the persona-based workspace that layers experiments, the Feature Store, AutoML, the Model Registry and Model Serving on top of that Lakehouse.

The Databricks Runtime for Machine Learning (ML Runtime) pre-installs popular libraries — scikit-learn, XGBoost, TensorFlow, PyTorch, Hyperopt and MLflow — and bakes in GPU drivers, so you spend your time modelling rather than configuring clusters.

The Professional exam assumes you can move fluently between notebooks, jobs, clusters, the experiments UI and the registry without friction. Knowing where each capability lives is the foundation for every later module.

🔷 Databricks ML Professional Exam Prep