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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Modeling and Machine Learning Basics | 20% | - Model performance and optimization
|
| Topic 2: Data Visualization and Communication | 15% | - Data storytelling and reporting
|
| Topic 3: SQL and Database Integration | 10% | - Relational database concepts
|
| Topic 4: Data Acquisition and Preprocessing | 30% | - Data preparation with Pandas and NumPy
|
| Topic 5: Data Exploration and Statistical Analysis | 25% | - Exploratory data analysis
|
1. Which characteristics are typically associated with supervised learning algorithms?
(Choose two)
A) They automatically detect outliers
B) They work only with numerical features
C) They are useful for regression and classification tasks
D) They require labeled training data
2. What is a key advantage of using the Parquet file format over CSV in large-scale data pipelines?
A) Parquet stores data in plain text, making it human-readable
B) Parquet files can only be used with Excel
C) Parquet supports schema evolution and columnar storage
D) Parquet offers row-based compression
3. What is the most appropriate way to ensure that a column used as a foreign key contains only valid references to a parent DataFrame in Pandas?
A) Use df.dropna() on the foreign key column
B) Use df.merge() with how='outer'
C) Use .isin() to compare the foreign key column against the parent key column
D) Use df.sort_values() to sort both columns before merging
4. Why is it important to adjust data presentations based on the audience's background?
A) To ensure the data is understood and supports actionable insights
B) To include as many technical terms as possible
C) To avoid using charts altogether
D) To simplify all metrics to percentages only
5. Which file formats are commonly used for hierarchical or nested data structures in data acquisition?
(Choose two)
A) CSV
B) TSV
C) XML
D) JSON
Solutions:
| Question # 1 Answer: C,D | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: C,D |
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