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Python Institute PCAD-31-02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Acquisition and Pre-Processing | 29.2% | |
| Topic 2: Statistical Methods and Modeling | ||
| Topic 3: Exploratory Data Analysis | ||
| Topic 4: Data Visualization and Communication | ||
| Topic 5: SQL and Data Management |
Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:
Which practices are essential to ensure a fair evaluation of a machine learning model's performance?
(Choose two)
- A. Using cross-validation to assess generalizability
- B. Training on the entire dataset including test records
- C. Randomizing the test dataset labels
- D. Splitting data into training and test sets
Correct Answer: A,D 🗳️
Which method is commonly used to handle missing numerical data in a dataset?
- A. Replacing with text labels
- B. Dropping all columns
- C. Multiplying all missing values by zero
- D. Filling with the mean or median
Correct Answer: D 🗳️
When analyzing a dataset of customer ages, you calculate the mean, median, and mode. What does it indicate if all three values are approximately equal?
- A. The dataset is positively skewed
- B. The dataset is uniformly distributed
- C. The dataset has a normal distribution
- D. The dataset contains outliers
Correct Answer: C 🗳️
What is a key assumption of linear regression that distinguishes it from logistic regression?
- A. Output values must be binary
- B. The target variable is unordered categorical
- C. Predictors must be independent
- D. The relationship between predictors and the outcome is linear
Correct Answer: D 🗳️
What is the purpose of using the groupby() function in a Pandas DataFrame when analyzing a dataset with multiple categories and numerical values?
- A. To append new rows to the DataFrame
- B. To sort the DataFrame by a specific column
- C. To split the data into subgroups for aggregation
- D. To filter rows based on index values
Correct Answer: C 🗳️
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