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Databricks Databricks-Machine-Learning-Professional Exam Overview:
| Certification Vendor: | Databricks |
|---|---|
| Exam Name: | Databricks Certified Machine Learning Professional |
| Exam Number: | Databricks-Machine-Learning-Professional |
| Exam Price: | USD 200 |
| Exam Format: | Multiple choice |
| Passing Score: | 70% |
| Certificate Validity Period: | 2 years |
| Related Certifications: | Databricks Certified Machine Learning Associate |
| Available Languages: | English |
| Real Exam Qty: | 60 |
| Exam Duration: | 120 minutes |
| Sample Questions: |  |
| Exam Way: | Online (proctored) or Test Center |
| Pre Condition: | 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). |
| Official Syllabus URL: | https://www.databricks.com/learn/certification/machine-learning-professional |
Databricks Databricks-Machine-Learning-Professional Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Model Deployment | 10% | - Deployment Strategies
|
| Topic 2: Model Development | 47% | - MLflow Advanced Features
|
| Topic 3: Model Lifecycle Management (MLOps) | 43% | - Testing Strategies
|
Answers About Databricks Certified Machine Learning Professional Preparation
The real Databricks-Machine-Learning-Professional exam gives you 120 minutes minutes to answer 60 questions. Practicing under the same constraints on the LatestCram engine makes the real pacing feel familiar.
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The package includes 193 practice questions for the Databricks-Machine-Learning-Professional exam. Candidates often note that the study thoughts behind them are concise and easy to absorb, which keeps revision efficient rather than tedious.
To pass Databricks-Machine-Learning-Professional you need 70%, and the official exam fee is USD 200. Knowing both figures early helps you plan your exam date and your practice target together.
Feedback from buyers is one of the strongest reasons new candidates trust us. Reviewers frequently mention passing smoothly and scoring well, and many describe the study thoughts as concise, easy to get, and definitely not boring. We would rather let their words speak than write our own slogans.
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).
- Model Lifecycle Management (MLOps) (43%)
- Model Deployment (10%)
- Model Development (47%)
Spend more time on the topics that carry the most weight.
Databricks Certified Machine Learning Professional Sample Questions:
Which of the following is an obstacle related to streaming machine learning applications?
- A. All of these
- B. End-to-end fault tolerance
- C. Out-of-order data
- D. None of these
Correct Answer: A 🗳️
Explanation: Only visible for LatestCram members. You can sign-up / login (it's free).
Which of the following statements about built-in library-specific MLflow Model flavors is true?
- A. Built-in library-specific flavors are required for model signature use
- B. Built-in library-specific flavors allow models to be used with any library/span>
- C. Built-in library-specific flavors can only be used for logging models
- D. Built-in library-specific flavors allow models to be exported as library objects
Correct Answer: D 🗳️
Explanation: Only visible for LatestCram members. You can sign-up / login (it's free).
A data scientist would like to enable MLflow Autologging for all machine learning libraries used in a notebook. They want to ensure that MLflow Autologging is used no matter what version of the Databricks Runtime for Machine Learning is used to run the notebook and no matter what workspace-wide configurations are selected in the Admin Console. Which of the following lines of code can they use to accomplish this task?
- A. mlflow.spark.autolog()
- B. mlflow.autolog()
- C. It is not possible to automatically log MLflow runs.
- D. mlflow.sklearn.autolog()
- E. spark.conf.set("autologging", True)
Correct Answer: E 🗳️
A data scientist has written a function to track the runs of their random forest model. The data scientist is changing the number of trees in the forest across each run. Which of the following MLflow operations is designed to log single values like the number of trees in a random forest?
- A. mlflow.log_metric
- B. mlflow.log_param
- C. There is no way to store values like this.
- D. mlflow.log_artifact
- E. mlflow.log_model
Correct Answer: A 🗳️
A data scientist has computed updated rows that contain new feature values for primary keys already stored in the Feature Store table features. The updated feature values are stored in the DataFrame features_df. They want to update the rows in features if the associated primary key is in features_df. If a row's primary key is not in features_df, they want the row to remain unchanged in features. Which code block can they use to perform this task using the Feature Store Client fs?
- A.
- B.
- C.
- D.
Correct Answer: B 🗳️
Explanation: Only visible for LatestCram members. You can sign-up / login (it's free).
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