100% Free PCED Practice Exam Questions (2026)

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Python Institute PCED Dumps & Practice Test Questions 2026

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Total 382 Questions | Updated On: Aug 03, 2026

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Question 1

Suppose you are working on a classification problem with an imbalanced dataset. Which of the following techniques would not be effective for addressing the issue?

A : Using accuracy as the evaluation metric

B : Using the Synthetic Minority Over-sampling Technique (SMOTE)

C : Using different evaluation metrics such as F1-score.

D : Under-sampling the majority class

Answer: A

Question 2

You have the following Pandas DataFrame with some missing values:

import pandas as pd

import numpy as np

df = pd.DataFrame(

{"A": [1, np.nan, 3], "B": [4, 5, np.nan], "C": [7, 8, 9]}

)

How would you fill the missing values in column 'A' with the mean value of that column?

A : df['A'] = df['A'].fillna(df['C'].mean())

B : df['A'].fillna(df['A'].mean(), inplace=True)

C : df.fillna({'A': df['A'].mean()})

D : df['A'].apply(lambda x: x.fillna(x.mean()))

Answer: B

Question 3

You have a dataset of a retail company's sales transactions, which includes details like customer ID, transaction amount, transaction date, and store ID. You're tasked with summarizing monthly revenue for each store. What would be the most appropriate data aggregation technique?

A : Group the data by store ID and sum the transaction amounts daily, then take the average to get the monthly revenue.

B : Group the data by customer ID and store ID, then sum the transaction amounts and divide by the number of unique customers for each month.

C : Group the data by transaction date and calculate the daily revenue, then aggregate this to the monthly level without considering store ID.

D : Group the data by store ID and sum the transaction amounts for each month.

Answer: D

Question 4

You have developed a logistic regression model for a classification task. After training, you notice that both the training and validation errors are high. Which of the following might be the problem with your model?

A : The learning rate is too high.

B : The model is overfitting the data.

C : The model is too complex.

D : The model is underfitting the data.

Answer: D

Question 5

Which of the following NumPy methods would you use to apply a function element-wise on a 1-D array, while maintaining the shape of the original array?

A : np.reshape()

B : np.apply_along_axis()

C : np.ravel()

D : np.vectorize()

Answer: D

Page: 1 / 77

Total 382 Questions | Updated On: Aug 03, 2026

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