Databricks Databricks Machine Learning Professional Databricks Certified Machine Learning Professional Online Training
Databricks Databricks Machine Learning Professional Online Training
The questions for Databricks Machine Learning Professional were last updated at Apr 21,2025.
- Exam Code: Databricks Machine Learning Professional
- Exam Name: Databricks Certified Machine Learning Professional
- Certification Provider: Databricks
- Latest update: Apr 21,2025
After a data scientist noticed that a column was missing from a production feature set stored as a Delta table, the machine learning engineering team has been tasked with determining when the column was dropped from the feature set.
Which of the following SQL commands can be used to accomplish this task?
- A . VERSION
- B . DESCRIBE
- C . HISTORY
- D . DESCRIBE HISTORY
- E . TIMESTAMP
Which of the following describes label drift?
- A . Label drift is when there is a change in the distribution of the predicted target given by the model
- B . None of these describe label drift
- C . Label drift is when there is a change in the distribution of an input variable
- D . Label drift is when there is a change in the relationship between input variables and target variables
- E . Label drift is when there is a change in the distribution of a target variable
Which of the following machine learning model deployment paradigms is the most common for machine learning projects?
- A . On-device
- B . Streaming
- C . Real-time
- D . Batch
- E . None of these deployments
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.sklearn.autolog()
- B . mlflow.spark.autolog()
- C . spark.conf.set(“autologging”, True)
- D . It is not possible to automatically log MLflow runs.
- E . mlflow.autolog()
A data scientist has developed a model model and computed the RMSE of the model on the test set. They have assigned this value to the variable rmse. They now want to manually store the RMSE value with the MLflow run.
They write the following incomplete code block:
Which of the following lines of code can be used to fill in the blank so the code block can successfully complete the task?
- A . log_artifact
- B . log_model
- C . log_metric
- D . log_param
- E . There is no way to store values like this.
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