Exam Name: Databricks Certified Machine Learning Associate Exam
Certification Provider: Databricks
Corresponding Certification: ML Data Scientist
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- Total Questions: 76
- Updated on: Oct 15, 2026
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- Total Questions: 76
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- Total Questions: 76
- Updated on: Oct 15, 2026
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Life throws up enough obstacles without adding exam friction. The Lead1Pass Databricks-Machine-Learning-Associate package removes three at once: 76 practice questions available the moment you pay, a year of free updates, and a Windows engine that simulates the real exam.
Databricks Databricks-Machine-Learning-Associate Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Model Development | 31% | - Building and Training Models
|
| Topic 2: ML Workflows | 19% | - Machine Learning Lifecycle
|
| Topic 3: Model Deployment | 12% | - Production Deployment
|
| Topic 4: Databricks Machine Learning | 38% | - Databricks ML Capabilities
|
Databricks-Machine-Learning-Associate Exam FAQ: Updates, Speed, Simulation
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.
The Databricks Certified Machine Learning Associate exam contains 45-48 to complete within 90 minutes. Timed simulation in the Lead1Pass 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 Databricks Machine Learning (38%), Model Development (31%), and ML Workflows (19%). The full list is in the topics section above, and Lead1Pass's 76 practice questions cover each one.
No formal prerequisite. Databricks recommends at least 6 months of hands-on experience with Databricks Machine Learning, Python, SQL, MLflow, AutoML, Feature Store, and machine learning workflows. Since requirements change over time, confirm the latest on the official Databricks exam page before scheduling.
The Databricks Certified Machine Learning Associate exam requires 70% to pass, and registration costs $200 USD. A failed attempt means paying the same fee again — a readiness check with the Lead1Pass engines before booking is the cheaper option.
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 Machine Learning Professional, Databricks Certified Data Engineer Associate. Candidates in 2026 start with Lead1Pass'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.
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 Lead1Pass help you apply theory and fill any gaps the training leaves.
Lead1Pass 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.
Online proctored exam or authorized testing center. Register for the Databricks Certified Machine Learning Associate exam through these official channels:
After booking, Lead1Pass delivers your practice questions within 1 minute — preparation starts the same day.
Databricks Certified Machine Learning Associate Sample Questions:
A data scientist wants to tune a set of hyperparameters for a machine learning model. They have wrapped a Spark ML model in the objective function objective_function and they have defined the search space search_space.
As a result, they have the following code block:
Which of the following changes do they need to make to the above code block in order to accomplish the task?
- A. Change fmin() to fmax()
- B. Change SparkTrials() to Trials()
- C. Reduce num_evals to be less than 10
- D. Remove the algo=tpe.suggest argument
- E. Remove the trials=trials argument
Correct Answer: B 🗳️
Explanation: Only visible for Lead1Pass members. You can sign-up / login (it's free).
A data scientist has created two linear regression models. The first model uses price as a label variable and the second model uses log(price) as a label variable. When evaluating the RMSE of each model by comparing the label predictions to the actual price values, the data scientist notices that the RMSE for the second model is much larger than the RMSE of the first model.
Which of the following possible explanations for this difference is invalid?
- A. The data scientist failed to take the log of the predictions in the first model prior to computing the RMSE
- B. The RMSE is an invalid evaluation metric for regression problems
- C. The data scientist failed to exponentiate the predictions in the second model prior to computing the RMSE
- D. The second model is much more accurate than the first model
- E. The first model is much more accurate than the second model
Correct Answer: B 🗳️
Explanation: Only visible for Lead1Pass members. You can sign-up / login (it's free).
A data scientist is using MLflow to track their machine learning experiment. As a part of each of their MLflow runs, they are performing hyperparameter tuning. The data scientist would like to have one parent run for the tuning process with a child run for each unique combination of hyperparameter values. All parent and child runs are being manually started with mlflow.start_run.
Which of the following approaches can the data scientist use to accomplish this MLflow run organization?
- A. They can start each child run with the same experiment ID as the parent run
- B. They can turn on Databricks Autologging
- C. They can start each child run inside the parent run's indented code block using mlflow.start runO
- D. They can specify nested=True when starting the child run for each unique combination of hyperparameter values
- E. They can specify nested=True when starting the parent run for the tuning process
Correct Answer: D 🗳️
Explanation: Only visible for Lead1Pass members. You can sign-up / login (it's free).
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. Reproducibility is achievable when using a train-validation split
- B. Fewer models need to be trained when using a train-validation split
- C. Fewer hyperparameter values need to be tested when using a train-validation split
- D. Bias is avoidable when using a train-validation split
- E. A holdout set is not necessary when using a train-validation split
Correct Answer: B 🗳️
What is the name of the method that transforms categorical features into a series of binary indicator feature variables?
- A. Leave-one-out encoding
- B. Target encoding
- C. Categorical
- D. String indexing
- E. One-hot encoding
Correct Answer: E 🗳️
Explanation: Only visible for Lead1Pass members. You can sign-up / login (it's free).
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