Question 1

You are evaluating a logistic regression model using the ROC curve. Which of the following is true regarding the Area Under the Curve (AUC)?

Options :

A : A model with an AUC of 0 performs better than one with an AUC of 1

B : A higher AUC indicates that the model has higher bias

C : A model with an AUC closer to 1 performs better than one closer to 0

D : A model with an AUC of 0.5 is an excellent model

Answer: C

Question 2

While transforming extracted data to fit operational needs, which of the following operations is least likely to be performed?

Options :

A : Data enrichment

B : Data normalization

C : Data archiving

D : Data type conversion

E : Data cleansing

Answer: C

Question 3

You're developing a Python script to collect real-time data from various weather stations. Which approach would best help you implement robust data validation procedures to ensure the reliability and accuracy of the data?

Options :

A : Use type hints in Python to enforce data types

B : Implement checksum validation for incoming data packets

C : Employ a schema validation library to enforce structure and type constraints

D : Accept data only from weather stations that use the latest sensor technology

Answer: C

Question 4

You are building a data pipeline that requires you to load data from an API, transform it, and then save it to a database. Which of the following is the best approach to structure your script for maintainability and reusability?

Options :

A : Use global variables to hold the data as it moves through the pipeline.

B : Implement all operations as nested loops inside a main loop.

C : Write the entire workflow in a single function.

D : Separate the loading, transforming, and saving operations into individual functions.

Answer: D

Question 5

Your Python script is giving you unexpected results in data analysis. Which of the following is generally not advisable for debugging this issue?

Options :

A : Review and validate data inputs and transformations

B : Use conditional breakpoints to isolate the problem

C : Examine the Python traceback to identify where the error originates

D : Suppress all exceptions using a general except block

Answer: D

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