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Python Institute PCAD-31-02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Modeling and Machine Learning Basics | 20% | - Model performance and optimization
|
| Topic 2: Data Visualization and Communication | 15% | - Visualization with Matplotlib and Seaborn
|
| Topic 3: SQL and Database Integration | 10% | - Python-database connectivity
|
| Topic 4: Data Acquisition and Preprocessing | 30% | - Data preparation with Pandas and NumPy
|
| Topic 5: Data Exploration and Statistical Analysis | 25% | - Inferential statistics
|
Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:
Which actions are valid techniques for handling erroneous categorical values in a dataset?
(Choose two)
- A. Removing rows with invalid labels
- B. Normalizing using min-max scaling
- C. Converting all values to integers
- D. Replacing inconsistent labels with a standardized value
Correct Answer: A,D 🗳️
Which type of regression is most appropriate when the response variable is categorical, such as predicting customer churn (Yes/No)?
- A. Logistic regression
- B. Decision tree regression
- C. Linear regression
- D. Polynomial regression
Correct Answer: A 🗳️
What does a Pearson correlation coefficient value of -0.9 imply about the relationship between two numerical variables?
- A. No correlation
- B. A strong negative linear relationship
- C. A moderate non-linear association
- D. A weak positive relationship
Correct Answer: B 🗳️
When merging two Pandas DataFrames using a common key, which parameters are essential to ensure accurate and conflict-free results?
(Choose two)
- A. dropna
- B. suffixes
- C. on
- D. ignore_index
Correct Answer: B,C 🗳️
What may occur if a model is evaluated using the same data it was trained on?
- A. Data leakage
- B. Overfitting
- C. Overgeneralization
- D. Underfitting
Correct Answer: B 🗳️
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