Last Updated: Aug 15, 2026
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| Section | Weight | Objectives |
|---|---|---|
| SQL and Database Integration | 10% | - Relational database concepts
|
| Data Exploration and Statistical Analysis | 25% | - Inferential statistics
|
| Data Acquisition and Preprocessing | 30% | - Data collection, integration and storage
|
| Data Modeling and Machine Learning Basics | 20% | - Model performance and optimization
|
| Data Visualization and Communication | 15% | - Visualization principles and best practices
|
1. Which of the following correctly demonstrates the use of parameterized queries using Python's sqlite3 module?
A) cursor.execute("SELECT * FROM users WHERE id = ?", user_id)
B) cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))
C) cursor.execute("SELECT * FROM users WHERE id = " + user_id)
D) cursor.execute("SELECT * FROM users WHERE id = ':id'", {'id': user_id})
2. What is a major challenge in aggregating data from multiple sources?
Response:
A) Duplicate records and format inconsistencies
B) Increased algorithmic complexity
C) Excessive disk space usage
D) Overfitting in predictive models
3. Which function is used to reshape a NumPy array without modifying the original data values?
A) resize()
B) reshape()
C) transpose()
D) flatten()
4. What is a key advantage of using the Parquet file format over CSV in large-scale data pipelines?
A) Parquet offers row-based compression
B) Parquet stores data in plain text, making it human-readable
C) Parquet supports schema evolution and columnar storage
D) Parquet files can only be used with Excel
5. What is the main reason to remove duplicate records before performing analysis?
A) It helps increase sample size
B) It avoids converting data to JSON format
C) It ensures training data is intentionally overfitted
D) It reduces redundancy that can skew statistical metrics
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: A | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: D |
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