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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:

1. In supervised learning, what is the primary goal when training a model on labeled data?

A) To discover hidden patterns without outputs
B) To learn a function that maps inputs to known outputs
C) To cluster data points into similar groups
D) To analyze unstructured data formats like text

2. Why is min-max scaling applied before using algorithms like K-Nearest Neighbors or SVM?

A) To make all features interpretable as binary values
B) To compress all values into integers
C) To prevent features with larger scales from dominating distance calculations
D) To convert strings into numeric values

3. What is the key difference between the .iloc[] and .loc[] accessors when working with Series or DataFrames?

A) .iloc[] allows label-based selection
B) .iloc[] is position-based, while .loc[] is label-based
C) .loc[] can only be used on Series
D) .loc[] does not allow slicing

4. When analyzing a sales dataset using Pandas, which of the following techniques help extract key insights by grouping and summarizing the data?
(Choose two)

A) Applying agg() to calculate multiple metrics like mean and max
B) Using groupby() to compute total sales per region
C) Using fillna() to replace missing product prices
D) Using rename() to change column headers

5. Which conditions typically necessitate data normalization or scaling before analysis?
(choose two)

A) Distance-based modeling algorithms
B) Boolean feature encoding
C) Presence of duplicate data
D) Features with different units and scales

Solutions: