Directory / Databricks

Databricks Certified Machine Learning Associate

Classical machine learning on Databricks: feature engineering, training, tuning, evaluation and deployment. It has no generative AI content.

What it signals

Practical assessment: Scenario-based multiple choice. Proctored multiple-choice with code reading.
Identity assurance: Proctored with identity verification. Proctored; online proctored or test centre. No test aides.
Depth: Associate. Associate level.
Experience expected: Under 6 months. 6+ months recommended.
Portability: Mixed. General ML concepts mixed with Databricks tooling (AutoML, Feature Store, MLflow).
Verifiability: Public badge or registry. Public Accredible badge.

For hiring managers

Classical ML on Databricks; contains no generative AI content. Blueprint unchanged since March 2025.

Verifying it

Digital badge issued via Accredible at credentials.databricks.com (shareable URL an employer can open); holders may also opt in to the Databricks Certified Directory.

What it covers

Published exam outline

Databricks Machine Learning 38%
ML Workflows 19%
Model Development 31%
Model Deployment 12%

By topic

GenAI apps: Not covered. No foundation-model content.
Agents: Not covered. No agent content.
Classical ML: Core focus (over 35%). Model Development 31% plus ML Workflows 19% = 50% on training, tuning, evaluation.
Operations: Substantial (20 to 35%). Deployment 12% plus MLOps/MLflow/registry parts of the 38% platform section.
Data: Some (10 to 20%). Data exploration and feature engineering sit inside ML Workflows (19%) and the platform section.
Responsible AI: Not covered. Not in blueprint beyond Unity Catalog basics.

Exam details

Who the provider says it is for. Individuals who use Databricks to perform basic ML tasks: AutoML, Unity Catalog, MLflow, feature engineering, training/tuning/evaluation and deployment.

Format: Multiple choice / multiple selection (48 scored)
Delivery: Proctored; online proctored or test centre. No test aides.
Code or hands-on work: Code reading in multiple-choice items (Python; SQL for data manipulation). No labs.
Prerequisites: None
Recommended experience: 6+ months hands-on experience performing the ML tasks in the exam guide
Renewal: Retake the full current exam

Preparing

Not confirmed

These details were not available from an official source at the time of research.

passingScore (not published)
Precise split of the 38% 'Databricks Machine Learning' section between MLOps, feature store and AutoML topics

Sources (3)