Free study guide

Databricks Machine Learning Associate Study Guide

Databricks Certified Machine Learning Associate

The Databricks Certified Machine Learning Associate exam is for practitioners who complete basic machine learning tasks on Databricks. It covers AutoML, Feature Engineering in Unity Catalog, MLflow tracking and the Unity Catalog model registry, exploring and preparing data, training, tuning and evaluating models, and deploying them for batch, streaming and real-time inference.

  • Databricks certification
  • Associate level
  • 4 exam sections

This guide is free, with no sign-up. It explains every Databricks Machine Learning Associate exam topic in plain English, one chapter at a time. Read them in order or jump straight to the topic you need.

  • 4chapters
  • 16topics
  • 4diagrams and exhibits
  • 1 h 20 minfast track
Start with Databricks Machine Learning
  • Every topic follows the same simple pattern: what it is, how it works, common mistakes
  • Diagrams and real command output where a picture explains it best
  • Exam tips and worked subnetting and IPv6 practice, with answers

How the exam is weighted

Each domain is worth this share of the exam, so spend your study time in proportion. Select a domain to open its chapter.

Chapters

Open a chapter to see its topics and how long each takes.

1Databricks Machine Learning6 topics · 30 min fast trackMLOps, ML runtimes, AutoML, Unity Catalog feature tables, MLflow tracking, registry and aliases.
  1. 1MLOps Strategy, ML Runtimes and Promotion5 min
  2. 2AutoML for Model and Feature Selection5 min
  3. 3Feature Tables in Unity Catalog5 min
  4. 4Training and Scoring with Feature Tables5 min
  5. 5MLflow Runs, Manual Logging and the UI5 min
  6. 6Unity Catalog Model Registry, Tags and Aliases5 min
Read the chapter overview →
2Data Processing3 topics · 15 min fast trackSummary statistics, outliers, charts, imputing missing values, one-hot encoding and log scaling.
  1. 1Exploring Data: Summary Statistics, Outliers and Charts5 min
  2. 2Imputing Missing Values5 min
  3. 3One-Hot Encoding and Log Transformation5 min
Read the chapter overview →
3Model Development5 topics · 25 min fast trackAlgorithm choice, imbalance, Spark ML pipelines, Hyperopt tuning, cross validation, metrics.
  1. 1Algorithms, Imbalanced Data and Bias Variance5 min
  2. 2Estimators, Transformers and Training Pipelines5 min
  3. 3Hyperparameter Tuning with Hyperopt5 min
  4. 4Cross Validation and Grid Search5 min
  5. 5Classification and Regression Metrics5 min
Read the chapter overview →
4Model Deployment2 topics · 10 min fast trackBatch, streaming and real time serving, pandas inference, custom models and traffic splits.
  1. 1Batch, Streaming and Real Time Inference5 min
  2. 2Model Serving Endpoints and Traffic Splitting5 min
Read the chapter overview →

Ready for more practice?

The full Databricks Machine Learning Associate question bank has 600 questions, with timed practice exams and an explanation for every answer.

Get Full AccessTry Sample Exam

This study guide is independent and is not affiliated with, endorsed by, or sponsored by Databricks. Vendor names, certification names and exam codes are trademarks of their respective owners and are used for identification only.