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Databricks Certified Machine Learning Associate (Databricks Certified Machine Learning) - Databricks Exam Questions

Last updated on June 20, 2026

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74 Total Questions
1
Question
Which of the following describes the relationship between native Spark DataFrames and pandas API on Spark DataFrames?
Options
A pandas API on Spark DataFrames are less mutable versions of Spark DataFrames
B pandas API on Spark DataFrames are unrelated to Spark DataFrames
C pandas API on Spark DataFrames are more performant than Spark DataFrames
D pandas API on Spark DataFrames are made up of Spark DataFrames and additional metadata
E pandas API on Spark DataFrames are single-node versions of Spark DataFrames with additional metadata
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2
Question
A data scientist has developed a linear regression model using Spark ML and computed the predictions in a Spark DataFrame preds_df with the following schema: prediction DOUBLE actual DOUBLE Which of the following code blocks can be used to compute the root mean-squared-error of the model according to the data in preds_df and assign it to the rmse variable?

Exhibit

Exhibit

A) B)
C) D)

Exhibit

Exhibit
Options
A Option B
B Option D
C Option C
D Option A
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3
Question
A machine learning engineer would like to develop a linear regression model with Spark ML to predict the price of a hotel room. They are using the Spark DataFrame train_df to train the model.

The Spark DataFrame train_df has the following schema:

Exhibit

task?

The machine learning engineer shares the following code block: Which of the following changes does the machine learning engineer need to make to complete the
Options
A They need to convert the features column to be a vector
B They need to split the features column out into one column for each feature
C They need to utilize a Pipeline to fit the model
D They do not need to make any changes
E They need to call the transform method on train df
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4
Question
A data scientist has developed a machine learning pipeline with a static input data set using Spark ML, but the pipeline is taking too long to process. They increase the number of workers in the cluster to get the pipeline to run more efficiently. They notice that the number of rows in the training set after reconfiguring the cluster is different from the number of rows in the training set prior to reconfiguring the cluster.

Which of the following approaches will guarantee a reproducible training and test set for each model?
Options
A Manually partition the input data
B Write out the split data sets to persistent storage
C Set a speed in the data splitting operation
D Manually configure the cluster
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5
Question
A machine learning engineer wants to parallelize the inference of group-specific models using the Pandas Function API. They have developed the apply_model function that will look up and load the correct model for each group, and they want to apply it to each group of DataFrame df.

They have written the following incomplete code block:

Exhibit

Which piece of code can be used to fill in the above blank to complete the task?
Options
A predict
B groupedApplyInPandas
C mapInPandas
D applyInPandas
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