DATABRICKS-ML-ASSOCIATE Practice Test

DATABRICKS-ML-ASSOCIATE practice test: what's covered

• Databricks ML
• ML Workflows
• Model Development
• MLflow
• Deployment
• Governance

Free DATABRICKS-ML-ASSOCIATE sample questions

1. A Databricks ML practitioner is validating databricks machine learning workspace for Databricks ML Associate and must use Databricks ML capabilities in the right workspace context. Which response is the BEST fit?

   • A. Use appropriate Databricks ML workspace features, notebooks and compute for the model task
   • B. Run all ML work on a personal laptop outside governed workspace controls
   • C. Use an oversized all-purpose cluster for every experiment forever
   • D. Share notebook results by copying screenshots only
   Show answer

   Correct: A. Use appropriate Databricks ML workspace features, notebooks and compute for the model task is the best answer because Databricks ML work depends on the right workspace, compute, notebooks, permissions and platform features. The other choices do not fit the scenario: Run all ML work on a personal laptop outside governed workspace controls addresses the wrong layer or timing, Use an oversized all-purpose cluster for every experiment forever skips a required control, and Share notebook results by copying screenshots only would create avoidable operational or security risk.

2. During a production rollout, a databricks ml practitioner needs to handle multiple teams sharing notebooks, clusters and ML assets without weakening databricks machine learning workspace. Which response is the BEST fit?

   • A. Select compute settings that support the required libraries, data access and collaboration pattern
   • B. Use an oversized all-purpose cluster for every experiment forever
   • C. Share notebook results by copying screenshots only
   • D. Bypass Databricks ML features because notebooks are enough
   Show answer

   Correct: A. Select compute settings that support the required libraries, data access and collaboration pattern is the best answer because Databricks ML work depends on the right workspace, compute, notebooks, permissions and platform features. The other choices do not fit the scenario: Use an oversized all-purpose cluster for every experiment forever addresses the wrong layer or timing, Share notebook results by copying screenshots only skips a required control, and Bypass Databricks ML features because notebooks are enough would create avoidable operational or security risk.

3. A review board asks for two actions that support use Databricks ML capabilities in the right workspace context while reducing unmanaged compute or assets that break collaboration and governance. Which TWO choices should the engineer select? (Choose TWO)

   • A. Use appropriate Databricks ML workspace features, notebooks and compute for the model task
   • B. Apply workspace permissions and object organization so teams can reproduce ML work
   • C. Run all ML work on a personal laptop outside governed workspace controls
   • D. Bypass Databricks ML features because notebooks are enough
   Show answer

   Correct: A and B. Use appropriate Databricks ML workspace features, notebooks and compute for the model task and Apply workspace permissions and object organization so teams can reproduce ML work are correct because Databricks ML work depends on the right workspace, compute, notebooks, permissions and platform features. The distractors do not satisfy the requirement: Run all ML work on a personal laptop outside governed workspace controls is incomplete for this case, and Bypass Databricks ML features because notebooks are enough solves a different problem or weakens the design.

4. An audit finding shows unmanaged compute or assets that break collaboration and governance in databricks machine learning workspace for a regulated production environment. Which response is the BEST fit?

   • A. Apply workspace permissions and object organization so teams can reproduce ML work
   • B. Share notebook results by copying screenshots only
   • C. Bypass Databricks ML features because notebooks are enough
   • D. Run all ML work on a personal laptop outside governed workspace controls
   Show answer

   Correct: A. Apply workspace permissions and object organization so teams can reproduce ML work is the best answer because Databricks ML work depends on the right workspace, compute, notebooks, permissions and platform features. The other choices do not fit the scenario: Share notebook results by copying screenshots only addresses the wrong layer or timing, Bypass Databricks ML features because notebooks are enough skips a required control, and Run all ML work on a personal laptop outside governed workspace controls would create avoidable operational or security risk.

5. A team is preparing a change window for databricks machine learning workspace and needs defensible evidence for exam-style review. Which response is the BEST fit?

   • A. Use platform-native ML tools rather than exporting work into unmanaged local scripts
   • B. Bypass Databricks ML features because notebooks are enough
   • C. Run all ML work on a personal laptop outside governed workspace controls
   • D. Use an oversized all-purpose cluster for every experiment forever
   Show answer

   Correct: A. Use platform-native ML tools rather than exporting work into unmanaged local scripts is the best answer because Databricks ML work depends on the right workspace, compute, notebooks, permissions and platform features. The other choices do not fit the scenario: Bypass Databricks ML features because notebooks are enough addresses the wrong layer or timing, Run all ML work on a personal laptop outside governed workspace controls skips a required control, and Use an oversized all-purpose cluster for every experiment forever would create avoidable operational or security risk.

Last updated: 2026-09-23

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