Requirements

• Working knowledge of Python and of machine learning libraries such as scikit-learn
• SparkML and MLflow. You do not need to be an expert
• but you should be able to read a code-level question without looking up basic syntax.,Some hands-on exposure to Databricks: notebooks
• Unity Catalog
• jobs and MLflow tracking. Databricks recommends around a year of practical experience for this exam.,These are practice tests
• not a course. They are designed to sit alongside the free official Databricks Academy learning paths and the product documentation
• and to tell you where to go back and study. They do not teach the platform from scratch.

Description

Who this course is for:

• Machine learning engineers
• data scientists and data engineers who are preparing for the Databricks Certified Machine Learning Professional exam and want to know whether they are ready before they pay to sit it. It suits practitioners who already build models on Databricks and now need to be sure they can answer questions about Unity Catalog model lifecycle management
• Databricks Asset Bundles
• automated retraining
• data profiling monitors and custom model serving under time pressure. It also suits engineers moving from a general MLOps background into Databricks specifically
• and Databricks Certified Machine Learning Associate holders taking the next step. Read this if you studied for this exam before autumn 2025. The exam changed on 30 September 2025. The previous version was organised around Experimentation
• Model Lifecycle Management
• Model Deployment
• and Solution and Data Monitoring. The current version is organised around Model Development
• MLOps and Model Deployment
• and it has moved substantially towards enterprise-scale operations: distributed tuning with Optuna and Ray
• the pandas Function API
• point-in-time correctness and on-demand features
• Databricks Asset Bundles
• automated retraining
• Lakehouse Monitoring (now documented as data profiling) and custom model serving. Older practice material still tests workspace model registry stages and registry webhooks
• which no longer reflect how models in Unity Catalog work. Every question in this course is written against the current exam guide. What this is: 295 questions with a detailed explanation for every answer option and a link to the official documentation
• so a wrong answer teaches you something. What this is not: a substitute for the official training
• for the documentation
• or for hands-on work in a Databricks workspace. No practice test can make you competent at a platform
• and none of these questions are real exam questions.