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CERTIFIED
Machine LearningAssociate
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Databricks Machine Learning Certification Prep

Databricks Certified Machine Learning Associate

Related topics Apache Spark, PySpark, Data Engineeringgroups 42,052 learnersOfficial exam page

Prepare on PySpark.in with study material, hands-on practice and timed mocks. Register officially on Databricks/Webassessor when you are ready.

Official exam redirectsComplete study pathMock review and readiness score
48full-mock questions
90 minexam-style timer
Rs. 300lifetime full mock
Official Exam Path
Questions45 scored
Time limit90 minutes
RegistrationDatabricks/Webassessor

PySpark.in prepares learners with independent practice. Official certification is always completed on Databricks.

Official Databricks Page
About the exam

Databricks Certified Machine Learning Associate

The Databricks Certified Machine Learning Associate exam assesses an individual’s ability to use Databricks to perform basic machine learning tasks. This includes understanding and using Databricks ML capabilities like AutoML, Unity Catalog and select features of MLflow; exploring data and performing feature engineering; building models through training, tuning, evaluation and selection; and deploying machine learning models. Individuals who pass can complete basic machine learning tasks using Databricks and its associated tools (scikit-learn, SparkML, Hyperopt, the Feature Store and MLflow).

Exam blueprint

Exam sections

Databricks Machine Learning (AutoML, Feature Store, MLflow)38%
Model Development (tuning, cross-validation, metrics)31%
ML Workflows / Data Processing & Feature Engineering19%
Model Deployment (batch, realtime, streaming)12%
Skills covered

What you should know

Databricks ML & AutoMLFeature Store in Unity CatalogMLflow Tracking & Model RegistryData Processing & Feature EngineeringModel Development & Tuning (Hyperopt)Model Deployment & Serving
Hands-on API usageDataFrame transformations, schemas, joins and aggregations.
Execution awarenessJobs, stages, shuffles, partitions and performance choices.
Production readinessTroubleshooting, tuning and working with common Spark workloads.
Step-by-step preparation guide

Start here and follow this plan until exam day

Use PySpark.in as the preparation hub: first verify the official Databricks exam details, then study every domain, practise hands-on and finish with timed mock tests.

Roadmap links open official Databricks documentation or registration pages. Use those pages for source-of-truth exam details, then return to PySpark.in for practice and mocks.

Step 1Understand the exam blueprint

Know the four sections, their weightings, the 48-question/90-minute format and the registration path before you study.

  • Read the official Machine Learning Associate exam guide and the summary on this page.
  • Note the weightings: Databricks ML (38%), Model Development (31%), ML Workflows (19%), Model Deployment (12%).
  • Confirm the $200 fee, 2-year validity, and that questions are multiple-choice or multiple-selection.
Step 2Databricks ML platform, AutoML & runtimes

Be fluent in the platform core: ML runtimes, AutoML and MLOps best practices.

  • Learn how AutoML automates feature/model selection and generates editable baseline notebooks.
  • Understand the advantages of Databricks ML runtimes and MLOps best practices.
  • Know when to promote code vs promote models.
Step 3Feature Store & MLflow (Unity Catalog)

Manage features and experiments: Feature Store in UC and MLflow tracking/registry.

  • Create a Feature Store table with FeatureEngineeringClient.create_table; train/score models from it.
  • Compare account-level vs workspace-level and online vs offline feature tables.
  • Log metrics/artifacts/models in MLflow, find the best run, and register models in the Unity Catalog registry with tags and champion/challenger aliases.
Step 4Data processing & feature engineering (19%)

Prepare data: summary stats, outliers, imputation, encoding and transforms.

  • Compute summary statistics (.summary()), remove outliers by std-dev/IQR, and visualize features.
  • Impute continuous features with mean/median (after checking the distribution) and categoricals with mode.
  • Apply one-hot encoding (and know when it is not appropriate) and log-scale transforms for skewed features.
Step 5Model development & tuning (31%)

The second-heaviest section: pipelines, hyperparameter tuning, cross-validation and metrics.

  • Select algorithms, mitigate class imbalance (cost-sensitive learning/resampling), and compare estimators vs transformers.
  • Tune with Hyperopt fmin (random/grid/Bayesian) and count models = param-combinations × CV folds.
  • Use classification (F1, Log Loss, ROC/AUC) and regression (RMSE, MAE, R²) metrics; exponentiate log-transformed targets; reason about bias-variance.
Step 6Model deployment & serving (12%)

Ship models: batch, realtime and streaming inference.

  • Compare batch, realtime and streaming serving; deploy a custom model to a Model Serving endpoint.
  • Query an endpoint for realtime inference and split traffic between endpoints for A/B tests.
  • Use pandas for batch inference and Delta Live Tables (model as Spark UDF) for streaming inference.
Mock-test strategy

Use mocks to decide when you are exam-ready

Do not book the official exam after one lucky score. Use short mocks for diagnosis, full mocks for stamina, and review every wrong answer before retrying.

Book the official exam when:You score 80%+ twice in full mocks, finish within 90 minutes, and can explain why each missed answer was wrong.
Databricks Certified Machine Learning Associate practice hub

Practise, pass and get your PySpark.in certificate automatically

Use the free mocks to diagnose weak areas, then take the full 48-question PySpark.in Machine Learning Certification Exam when you are ready for a certificate-backed assessment.

48 certificate exam questions90 min timed assessment70%+ certificate thresholdAuto certificate generation
Automatic PySpark.in certificate after passing

Once the PySpark.in Machine Learning Certification Exam is cleared with 70% or higher, the platform generates a downloadable certificate with your name, score and certificate ID.

FREE MOCKMOCK-CMLA-20

Machine Learning Core Readiness Check

45 min20 questionsPass: 70%

A free 20-question timed mock weighted to the official blueprint across all four sections — Databricks ML, data processing, model development and deployment.

20 timed questionsBlueprint-weighted
FREE MOCKMOCK-CMLA-GUIDE

Machine Learning Guide Sample Practice

15 min10 questionsPass: 70%

The official Databricks sample questions from the Machine Learning Associate exam guide plus warm-ups — the closest look at how the real certification questions are phrased.

Official sample questionsFast warm-up
Official exam path

Official exam links and extra learning options

Use Databricks links for source-of-truth exam details, voucher rules and booking. Use PySpark.in practice resources and selected courses to prepare with confidence.

Official DatabricksExam, vouchers and registration

Redirect users to Databricks/Webassessor for source-of-truth exam details, voucher events and booking.

PySpark.inPreparation support

Use full mocks, answer explanations, notes, cheat sheets, training support and selected course resources to strengthen your exam readiness.

PySpark.in is independent and not affiliated with Databricks. Official vouchers, registration, proctoring and certification decisions are handled only by Databricks/Webassessor. External course links may be partner links at no extra cost to you.