What is the primary purpose of Markdown cells in a Jupyter notebook?

To add formatted documentation and explanations

A data scientist is training a Random Forest classifier on a dataset with many categorical features. They want to use Scikit-learn's pipeline to preprocess the data and train the model in one step. Which pipeline configuration is appropriate?

Pipeline([('preprocess', ColumnTransformer([('num', StandardScaler(), numeric_cols), ('cat', OneHotEncoder(), cat_cols)])), ('clf', RandomForestClassifier())])

Pipeline([('preprocess', OneHotEncoder()), ('clf', RandomForestClassifier())])

Pipeline([('preprocess', StandardScaler()), ('clf', RandomForestClassifier())])

Pipeline([('clf', RandomForestClassifier())])

A data scientist wants to visualize the distribution of a numeric column 'age' from a DataFrame to check for skewness and outliers. Which plotting approach is most appropriate?

sns.scatterplot(data=df, x='age', y='age')

sns.barplot(data=df, x='age', y='age')

sns.lineplot(data=df, x='age', y='age')

sns.histplot(data=df, x='age', kde=True)

GIAC Machine Learning Engineer

Domain 1Objective 2

Leveraging Python GMLE Practice Questions (Page 5)

Part of the Foundational Data Science and Statistics domain, which makes up ~41% of our current practice bank. GIAC (SANS) does not publish an official question count, but from its 180-minute exam (~70–120 total, ~29–49 in this domain), expect 7–12 from this objective — we provide 36 practice questions to prepare you well beyond it. (estimate)

36questions here

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Questions 21–25

21foundation · easy
What is the primary purpose of Markdown cells in a Jupyter notebook?
Select an answer first
22application · medium
A data scientist is training a Random Forest classifier on a dataset with many categorical features. They want to use Scikit-learn's pipeline to preprocess the data and train the model in one step. Which pipeline configuration is appropriate?
Select an answer first
23foundation · easy
What is the output of the following Python code? x = 5 if x > 3: print('large') else: print('small')
Select an answer first
24application · medium
A data scientist wants to visualize the distribution of a numeric column 'age' from a DataFrame to check for skewness and outliers. Which plotting approach is most appropriate?
Select an answer first
25foundation · easy
What is the result of the following Python code? my_dict = {'a': 1, 'b': 2} print(my_dict['a'])
Select an answer first

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Leveraging Python GMLE Practice Questions (Page 5)

Questions 21–25

What is the primary purpose of Markdown cells in a Jupyter notebook?

A data scientist is training a Random Forest classifier on a dataset with many categorical features. They want to use Scikit-learn's pipeline to preprocess the data and train the model in one step. Which pipeline configuration is appropriate?

What is the output of the following Python code? x = 5 if x > 3: print('large') else: print('small')

A data scientist wants to visualize the distribution of a numeric column 'age' from a DataFrame to check for skewness and outliers. Which plotting approach is most appropriate?

What is the result of the following Python code? my_dict = {'a': 1, 'b': 2} print(my_dict['a'])

Keep studying — Foundational Data Science and Statistics