Databricks Certified Machine Learning Associate Exam Nov '25

About this course

Prepare with confidence for the Databricks Certified Machine Learning Associate Exam (Nov ’25) — a complete, guide designed to help you master Databricks Machine Learning essentials and pass the exam on your first attempt.This course covers every topic area outlined in the official Databricks exam guide, including Databricks ML workspace features, AutoML, Unity Catalog, Delta Live Tables, MLflow tracking, model development, tuning, and deployment. You’ll gain knowledge about Python, scikit-learn, and SparkML within Databricks notebooks, and simulated exam-style questions.You’ll also learn how to:Explore and prepare data for machine learning efficiently using Databricks.Build, tune, and evaluate ML models with Spark MLlib and AutoML.Identify the best practices of an MLOps strategy DatabricksIdentify the advantages of using ML runtimes DatabricksIdentify how AutoML facilitates model/feature selection. DatabricksIdentify the advantages AutoML brings to the model development process DatabricksIdentify the benefits of creating feature store tables at the account level in Unity Catalog inScore a model using features from a feature store table. DatabricksDescribe the differences between online and offline feature tables DatabricksIdentify the best run using the MLflow Client API. DatabricksTrack experiments, register models, and deploy them using MLflow.Manage permissions, lineage, and reproducibility with Unity Catalog.Apply exam strategies and handle scenario-based questions confidently.Choose the most appropriate metric for a given scenario objective DatabricksIdentify the need to exponentiate log-transformed variables before calculating evaluationmetrics or interpreting pred