| title | ML Associate | |||
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| type | certification | |||
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Important
What changed in the March 1, 2025 exam guide
- 4 domains with explicit weights: Databricks ML 38 %, Model Development 31 %, ML Workflows 19 %, Model Deployment 12 %
- Stronger emphasis on Unity Catalog for ML (model registry, feature tables, inference tables)
- AutoML as a first-class skill within Databricks ML
- Pass / fail — the March 1, 2025 exam guide does not publish a numeric passing score
The official source of truth: Databricks Certified Machine Learning Associate. The folder structure in this guide now matches the official 4-domain blueprint 1 : 1.
| Detail | Information |
|---|---|
| Certification | Databricks Certified Machine Learning Associate |
| Exam guide | March 1, 2025 |
| Scored questions | 48 multiple-choice |
| Duration | 90 minutes |
| Result | Pass / fail (no numeric threshold in the March 1, 2025 exam guide) |
| Languages | English, Japanese, Portuguese (BR), Korean |
| Code in stems | Python (ML); SQL for non-ML supporting tasks |
| Experience | 6+ months hands-on ML on Databricks (recommended) |
| Recertification | Every 2 years — see Renewal Guide |
| Cost | $200 USD |
| Delivery | Online proctored or test center |
pie title Exam Topic Distribution (4 domains)
"Databricks Machine Learning" : 38
"Model Development" : 31
"ML Workflows" : 19
"Model Deployment" : 12
| Section | Weight | Focus |
|---|---|---|
| 01 — Databricks Machine Learning | 38 % | ML workspace, compute, AutoML, UC for ML |
| 02 — Model Development | 31 % | Spark ML pipelines, feature engineering, Feature Store |
| 03 — ML Workflows | 19 % | MLflow tracking, experiments, end-to-end loop |
| 04 — Model Deployment | 12 % | Model Registry in UC, Model Serving, Inference Tables |
| Resource | Description |
|---|---|
| Practice Questions | Topic-specific practice questions |
| Mock Exam 1 | Full-length practice exam |
| Mock Exam 2 | Alternative practice exam |
| Exam Tips | Exam strategies and tips |
| Official Links | Documentation and resources |
After completing this certification, explore:
- Interview Prep Resource - System design, feature engineering, and model architecture questions
Review these shared fundamentals:
- Domain 01 — Databricks Machine Learning (AutoML, UC for ML)
- Domain 02 — Model Development (Spark ML, feature engineering, Feature Store)
- Domain 03 — ML Workflows (MLflow tracking, experiments)
- Domain 04 — Model Deployment (Model Registry, Model Serving)
- Run Hands-on Lab 04 (MLflow + Model Registry in UC)
Complete this certification before attempting ML Professional.