Databricks Databricks-Machine-Learning-Associate : Databricks Certified Machine Learning Associate Exam

  • Exam Code: Databricks-Machine-Learning-Associate
  • Exam Name: Databricks Certified Machine Learning Associate Exam
  • Updated: Oct 11, 2026
  • Q & A: 76 Questions and Answers

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About Databricks Databricks-Machine-Learning-Associate Exam

The exam will test knowledge; preparation tests discipline. In 2026, BraindumpsPrep supplies the structure for that discipline — 76 practice questions, verified answers, and tools that keep you honest.

Databricks Databricks-Machine-Learning-Associate Exam Syllabus Topics:

SectionWeightObjectives
Model Deployment12%- Model Registry and Serving
  • 1. Inference and monitoring basics
    • 2. Model versioning and staging
      • 3. Register models in Unity Catalog
        • 4. Model deployment options
          Model Development31%- Training, Tuning and Evaluation
          • 1. Model evaluation metrics
            • 2. Hyperparameter tuning with Hyperopt
              • 3. Algorithm selection
                • 4. Pipeline construction
                  - Data Preparation and Feature Engineering
                  • 1. Data exploration and cleaning
                    • 2. Handling class imbalance
                      • 3. Feature transformation and selection
                        ML Workflows19%- MLflow Tracking and Experimentation
                        • 1. Run logging and metrics
                          • 2. Experiment management
                            • 3. Artifacts and model logging
                              • 4. MLflow UI navigation
                                Databricks Machine Learning38%- Databricks ML Environment and Capabilities
                                • 1. AutoML usage
                                  • 2. Lakehouse for ML
                                    • 3. Feature Store concepts
                                      • 4. Unity Catalog for ML assets

                                        Databricks Certified Machine Learning Associate Exam: Experience-Built Preparation

                                        The Databricks Certified Machine Learning Associate exam contains 48 to complete within 90 minutes. Timed simulation in the BraindumpsPrep Desktop Test Engine teaches that rhythm before exam day does.

                                        The official Databricks Certified Machine Learning Associate outline defines 4 domains. The leading three are Model Deployment (12%), Databricks Machine Learning (38%), and Model Development (31%). The full list is in the topics section above, and BraindumpsPrep's 76 practice questions cover each one.

                                        Online proctored or in-person at authorized test centers Register for the Databricks Certified Machine Learning Associate exam through these official channels:

                                        After booking, BraindumpsPrep delivers your practice questions within 1 minute — preparation starts the same day.

                                        The Databricks-Machine-Learning-Associate exam is a Databricks certification exam validating the Databricks Certified Machine Learning Associate syllabus shown above. It belongs to these credential paths: Databricks Certified Data Analyst Associate, Databricks Certified Data Engineer Associate. Candidates in 2026 start with BraindumpsPrep's 76 practice questions, available as a printable PDF, a Windows Desktop Test Engine, and an Online Test Engine — three versions of the same materials.

                                        BraindumpsPrep issues a full refund if you take the Databricks Certified Machine Learning Associate exam within 60 days of purchase and do not pass. The policy does not apply if the exam is taken within 3 days of purchase, if the exam was never actually taken, or to free materials or expired orders, and the candidate name must match the payer name. Submit a scan of your enrollment slip and the official Score Report PDF within 2 days of the exam; claims are processed within 7 days. Alternatively, exchange for two free exam products of equal value and keep your original update service. Orders arrive by email within 1 minute — contact support if nothing arrives within 2 hours.

                                        The Databricks Certified Machine Learning Associate exam requires Not publicly disclosed to pass, and registration costs USD 200 (plus applicable taxes). A failed attempt means paying the same fee again — a readiness check with the BraindumpsPrep engines before booking is the cheaper option.

                                        No formal prerequisites; 6+ months hands-on Databricks ML experience recommended Since requirements change over time, confirm the latest on the official Databricks exam page before scheduling.

                                        Databricks recommends these training resources for the Databricks Certified Machine Learning Associate exam:

                                        Follow the training with steady self-testing — the 76 practice questions from BraindumpsPrep help you apply theory and fill any gaps the training leaves.

                                        Three versions of the same study materials: a printable, expert-prepared PDF with free demo download and instant access; a Desktop Test Engine for Windows with customizable simulation and timed modes that works offline; and an Online Test Engine for any browser on Windows, Mac, Android, and iOS with test history and performance review. All 76 practice questions are identical across versions. Every purchase includes 365 days of free updates, a 50% renewal discount afterward, and unlimited computer installations.

                                        Databricks Certified Machine Learning Associate Sample Questions:

                                        Question #1

                                        A machine learning engineer has been notified that a new Staging version of a model registered to the MLflow Model Registry has passed all tests. As a result, the machine learning engineer wants to put this model into production by transitioning it to the Production stage in the Model Registry.
                                        From which of the following pages in Databricks Machine Learning can the machine learning engineer accomplish this task?

                                        • A. The experiment page in the Experiments observatory
                                        • B. The model page in the MLflow Model Registry
                                        • C. The model version page in the MLflow Model Registry
                                        • D. The home page of the MLflow Model Registry
                                        Reveal Solution  Discussion  0

                                        Correct Answer: C  🗳️

                                        Explanation: Only visible for BraindumpsPrep members. You can sign-up / login (it's free).

                                        Question #2

                                        A data scientist learned during their training to always use 5-fold cross-validation in their model development workflow. A colleague suggests that there are cases where a train-validation split could be preferred over k-fold cross-validation when k > 2.
                                        Which of the following describes a potential benefit of using a train-validation split over k-fold cross-validation in this scenario?

                                        • A. A holdout set is not necessary when using a train-validation split
                                        • B. Bias is avoidable when using a train-validation split
                                        • C. Fewer hyperparameter values need to be tested when using a train-validation split
                                        • D. Reproducibility is achievable when using a train-validation split
                                        • E. Fewer models need to be trained when using a train-validation split
                                        Reveal Solution  Discussion  0

                                        Correct Answer: E  🗳️

                                        Question #3

                                        A data scientist is attempting to tune a logistic regression model logistic using scikit-learn. They want to specify a search space for two hyperparameters and let the tuning process randomly select values for each evaluation.
                                        They attempt to run the following code block, but it does not accomplish the desired task:

                                        Which of the following changes can the data scientist make to accomplish the task?

                                        • A. Replace the random_state=0 argument with random_state=1
                                        • B. Replace the GridSearchCV operation with ParameterGrid
                                        • C. Replace the GridSearchCV operation with RandomizedSearchCV
                                        • D. Replace the penalty= ['12', '11'] argument with penalty=uniform ('12', '11')
                                        • E. Replace the GridSearchCV operation with cross_validate
                                        Reveal Solution  Discussion  0

                                        Correct Answer: C  🗳️

                                        Explanation: Only visible for BraindumpsPrep members. You can sign-up / login (it's free).

                                        Question #4

                                        Which of the following statements describes a Spark ML estimator?

                                        • A. An estimator is an alqorithm which can be fit on a DataFrame to produce a Transformer
                                        • B. An estimator is a trained ML model which turns a DataFrame with features into a DataFrame with predictions
                                        • C. An estimator is an evaluation tool to assess to the quality of a model
                                        • D. An estimator is a hyperparameter arid that can be used to train a model
                                        • E. An estimator chains multiple alqorithms toqether to specify an ML workflow
                                        Reveal Solution  Discussion  0

                                        Correct Answer: A  🗳️

                                        Explanation: Only visible for BraindumpsPrep members. You can sign-up / login (it's free).

                                        Question #5

                                        A data scientist is wanting to explore the Spark DataFrame spark_df. The data scientist wants visual histograms displaying the distribution of numeric features to be included in the exploration.
                                        Which of the following lines of code can the data scientist run to accomplish the task?

                                        • A. dbutils.data(spark_df).summarize()
                                        • B. spark_df.summary()
                                        • C. dbutils.data.summarize (spark_df)
                                        • D. spark_df.describe()
                                        • E. This task cannot be accomplished in a single line of code.
                                        Reveal Solution  Discussion  0

                                        Correct Answer: C  🗳️

                                        Explanation: Only visible for BraindumpsPrep members. You can sign-up / login (it's free).

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