In 2026, support that is actually available matters most when your exam is days away. Lead2Passed staffs its service around the clock, so questions about the Databricks Certified Machine Learning Professional material — or the 193 practice questions inside it — get answers when you need them.
Databricks Databricks-Machine-Learning-Professional Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Model Deployment | 10% | - Deployment Strategies
|
| Topic 2: Model Development | 47% | - SparkML and Scaling
|
| Topic 3: Model Lifecycle Management (MLOps) | 43% | - Monitoring
|
Databricks-Machine-Learning-Professional Exam FAQ
The Databricks Certified Machine Learning Professional exam requires a score of 70% to pass, and the official registration fee is USD 200. Knowing these numbers in advance keeps your planning honest.
Each round of the Databricks-Machine-Learning-Professional question bank starts from the official exam objectives: experts map the syllabus, draft questions to cover it with precision, and review the result before release. When new exam points appear, the bank is updated accordingly — deliberate coverage, not guesswork.
Any details you leave with us during browsing or purchase are guarded against misuse and external threats, and they are used only to deliver your order and support. Your Databricks-Machine-Learning-Professional purchase stays between you and us — that is a standing commitment, not a marketing line.
The Databricks Certified Machine Learning Professional exam contains 60 questions, and you will have 120 minutes minutes to complete them. Practicing under the same constraints makes exam-day pacing feel rehearsed.
No formal prerequisites, but 1+ years of hands-on experience performing the machine learning tasks outlined in the exam guide is highly recommended. Recommended courses: Machine Learning at Scale and Advanced Machine Learning Operations (instructor-led or self-paced via Databricks Academy).
You can confirm the current eligibility requirements on the official Databricks-Machine-Learning-Professional exam page before you register.
This package includes 193 practice questions for the Databricks Certified Machine Learning Professional exam. Every answer is verified by an experienced team of experts, so you can trust what you study.
The Databricks Certified Machine Learning Professional practice questions are organized around the official exam objectives. Key topics include:
- Model Deployment (10%)
- Model Lifecycle Management (MLOps) (43%)
- Model Development (47%)
Syllabus-driven coverage means no wasted practice on irrelevant material.
Databricks Certified Machine Learning Professional Sample Questions:
A data scientist has computed updated feature values for all primary key values stored in the Feature Store table features. In addition, feature values for some new primary key values have also been computed. The updated feature values are stored in the DataFrame features_df. They want to replace all data in features with the newly computed data. Which of the following code blocks can they use to perform this task using the Feature Store Client fs?
- A.
- B.
- C.
- D.
- E.
Correct Answer: C 🗳️
A Machine Learning Engineer needs to develop a custom anomaly detection model that monitors the internal IT infrastructure of their company. The model takes in compute metrics, logs, and user data and generates a binary prediction. The engineer plans to deploy it as a Databricks Model Serving endpoint. In production there will only be one client calling the endpoint once every
15 seconds. Leadership sees the model as an important part of their operational improvement strategy so maintaining consistent, stable, low latency inference is a requirement while minimizing infrastructure costs. The engineer plans to deploy the endpoint via the MLflow Deployment SDK.
Which endpoint config for the MLflow Deployment SDK should the engineer select?
- A.
- B.
- C.
- D.
Correct Answer: A 🗳️
Explanation: Only visible for Lead2Passed members. You can sign-up / login (it's free).
Which component manages model versions?
- A. MLflow Tracking
- B. Model Registry
- C. Feature Store
- D. Spark ML
Correct Answer: B 🗳️
Explanation: Only visible for Lead2Passed members. You can sign-up / login (it's free).
Which MLflow operation can be used to log a plot that was generated during an MLflow run?
- A. mlflow.log_metric
- B. mlflow.log_visualization
- C. mlflow.log_figure
- D. None of these operations can accomplish the task.
Correct Answer: C 🗳️
Explanation: Only visible for Lead2Passed members. You can sign-up / login (it's free).
Which of the following describes batch deployment for machine learning projects?
- A. None of these describe batch deployment for machine learning projects
- B. Predictions are computed prior to delivery and stored for later querying
- C. Predictions are computed and delivered as soon as feature values are available
- D. Predictions are computed immediately as data arrives and stored for later querying
Correct Answer: B 🗳️
Explanation: Only visible for Lead2Passed members. You can sign-up / login (it's free).
Viewing page 1 out of 39 pages.
Viewing questions 1-5 out of 193 questions.
1131 Customer Reviews
