Databricks ML Associate exam format
Here is what Databricks publishes about the Machine Learning Associate exam.
| Certification | Databricks Certified Machine Learning Associate |
| Scored questions | 48 |
| Duration | 90 minutes |
| Question format | Multiple choice |
| Registration fee | $200 |
| Validity | 2 years, then recertification |
| Prerequisites | None, though related training is recommended |
| Recommended experience | 6+ months hands-on with the exam’s ML tasks |
| Delivery | Online proctored or test centre |
| Languages | English, Japanese, Portuguese (BR), Korean |
| Test aids | None permitted |
| Passing score | Not published by Databricks |
Under two minutes per question
48 scored questions in 90 minutes is about 112 seconds each. Slightly tighter than the Generative AI Engineer exam, which allows two minutes. Not pressured, but not leisurely either.
Multiple choice throughout — no ordering, matching or drag-and-drop.
Python, with some SQL
Databricks states that all machine learning code on the exam is in Python. Where workflows or code are not ML-specific, data manipulation may be shown in SQL.
Practical implication: you must be able to read Python ML code and say what it does. You are not writing it from scratch under time pressure, but code-reading fluency is assumed throughout.
Section weighting
| Section | Weight | Approx. scored questions |
|---|---|---|
| Databricks Machine Learning | 38% | ~18 |
| ML Workflows | 19% | ~9 |
| Model Development | 31% | ~15 |
| Model Deployment | 12% | ~6 |
Counts derived from Databricks’ percentages against 48 scored questions.
Two things stand out.
The platform section is the largest. At 38%, Databricks Machine Learning — AutoML, Unity Catalog, MLflow and the ML-specific features of the workspace — outweighs model development. This is a platform exam as much as an ML exam, and candidates who revise machine learning theory while neglecting the tooling misallocate their time badly.
Deployment is only 12%. About six questions. If you come from an engineering background expecting pipelines and serving to dominate, adjust your expectations — that emphasis belongs to the professional-level exam.
The passing score is not published
Databricks does not publish one for this exam. Be sceptical of specific figures elsewhere unless they cite Databricks. Aim for consistent 80%+ on realistic practice material.
Two-year validity
Shorter than AWS’s three years. Recertification is required to stay current, so treat it as a recurring commitment rather than a one-off.
What the exam is really about
Databricks describes it as assessing the ability to “use Databricks to perform basic machine learning tasks”. The word doing the work is use. You are being tested on whether you can operate the platform’s ML capabilities competently — run an AutoML experiment, track runs in MLflow, register and govern a model, and understand the modelling decisions along the way.
Deep statistical knowledge is not the target. Platform fluency is.
Booking
Book through Databricks. Nothing gates registration, but the recommended six months of hands-on experience is realistic — this exam is much harder without having actually used MLflow and AutoML.