A new data science team member needs to set up a Python environment on their laptop to work on a project that uses Pandas, NumPy, and Scikit-learn. The team uses different projects with different dependencies. What is the recommended approach?

Install the libraries globally using pip install pandas numpy scikit-learn.

Create a virtual environment for the project and install the required libraries with pip.

Download the libraries as wheel files and manually place them in the project folder.

Use the system Python without any environment management.

GIAC Machine Learning Engineer

Domain 1Objective 2

Leveraging Python GMLE Practice Questions (Page 2)

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

8free pages

8concepts

Questions 6–10

6foundation · easy
Which command is used to install the pandas library into the active Python environment?
Select an answer first
7application · medium
A new data science team member needs to set up a Python environment on their laptop to work on a project that uses Pandas, NumPy, and Scikit-learn. The team uses different projects with different dependencies. What is the recommended approach?
Select an answer first
8foundation · easy
Which Seaborn function is specifically designed to create a histogram with a kernel density estimate (KDE) overlay?
Select an answer first
9foundation · easy
Which file format is used to save a Jupyter notebook?
Select an answer first
10foundation · easy
Which Pandas method is used to read a CSV file into a DataFrame?
Select an answer first

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Leveraging Python GMLE Practice Questions (Page 2)

Questions 6–10

Which command is used to install the pandas library into the active Python environment?

A new data science team member needs to set up a Python environment on their laptop to work on a project that uses Pandas, NumPy, and Scikit-learn. The team uses different projects with different dependencies. What is the recommended approach?

Which Seaborn function is specifically designed to create a histogram with a kernel density estimate (KDE) overlay?

Which file format is used to save a Jupyter notebook?

Which Pandas method is used to read a CSV file into a DataFrame?

Keep studying — Foundational Data Science and Statistics