Databricks Machine Learning Professional (ML-PRO)

This section targets ML-PRO, the Databricks Machine Learning Professional exam. It focuses on production ML systems: feature lifecycle, model registry workflows, controlled deployment, monitoring, drift, and governance. The exam rewards candidates who can reason about versioning, rollback, lineage, and safe release patterns instead of only training models offline.

Use the cheat sheet for rapid production-ML review. Use the FAQ for study and role-fit questions, and use the resources page when you need official Databricks references.

In this section

• ML-PRO Study Plan (30 / 60 / 90 Days)
  A practical ML-PRO study plan you can follow: 30-day intensive, 60-day balanced, and 90-day part-time schedules with weekly focus and MLOps-first practice tips.
• ML-PRO Cheatsheet — Production ML on Databricks (Features, Registry, Deployment, Monitoring)
  Last-mile ML-PRO review: feature pipeline patterns, MLflow registry and promotion workflows, batch vs online deployment pickers, monitoring/drift decision rules, and governance essentials.
• ML-PRO FAQ — Databricks Machine Learning Professional Questions Answered
  Common ML-PRO questions answered: prerequisites, what to focus on (MLOps, governance, deployment), how long to study, and how to practice effectively.