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| Section | Weight | Objectives |
|---|---|---|
| Data Acquisition and Pre-Processing | 29.2% | |
| Data Visualization and Communication | ||
| Statistical Methods and Modeling | ||
| SQL and Data Management | ||
| Exploratory Data Analysis |
1. Which Python construct allows you to iterate over a list of dictionary values and apply conditional logic to accumulate numerical values that meet a certain threshold?
A) lambda expression with reduce
B) filter() function with map
C) while loop with try block
D) for loop with if condition
2. What is the primary purpose of using a requirements.txt file in Python-based data projects?
A) To list the packages and versions required for consistent environment setup
B) To automatically compress source code for deployment
C) To store the current working directory of Python modules
D) To track script runtime dependencies during execution
3. In supervised learning, what is the primary goal when training a model on labeled data?
A) To learn a function that maps inputs to known outputs
B) To discover hidden patterns without outputs
C) To analyze unstructured data formats like text
D) To cluster data points into similar groups
4. What is a key advantage of using the Parquet file format over CSV in large-scale data pipelines?
A) Parquet supports schema evolution and columnar storage
B) Parquet files can only be used with Excel
C) Parquet offers row-based compression
D) Parquet stores data in plain text, making it human-readable
5. Which practices contribute to better exception handling in data pipelines involving file I/O and numerical computations?
(Choose two)
A) Using specific exception types like FileNotFoundError or ZeroDivisionError
B) Suppressing all error output using pass
C) Catching all exceptions using a generic except: clause without specifying the error
D) Logging error messages for later inspection during failures
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A | Question # 3 Answer: A | Question # 4 Answer: A | Question # 5 Answer: B,D |
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