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| Section | Weight | Objectives |
|---|---|---|
| Data Visualization and Communication | 15% | - Visualization principles and best practices
|
| SQL and Database Integration | 10% | - Relational database concepts
|
| Data Modeling and Machine Learning Basics | 20% | - Model performance and optimization
|
| Data Acquisition and Preprocessing | 30% | - Data cleaning and validation
|
| Data Exploration and Statistical Analysis | 25% | - Inferential statistics
|
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NEW QUESTION # 112
Which actions are valid techniques for handling erroneous categorical values in a dataset?
(Choose two)
Answer: C,D
NEW QUESTION # 113
Which of the following statements best describes the structural relationship between Pandas Series and DataFrames?
Answer: C
NEW QUESTION # 114
Which actions are considered part of basic data validation tasks in Python using Pandas?
(Choose two)
Answer: A,B
NEW QUESTION # 115
Which of the following are true characteristics of bootstrapping in statistics?
(Choose two)
Answer: A,B
NEW QUESTION # 116
What is the outcome of the following code?
data = [5, 10, 15]
result = [x**2 for x in data if x > 5]
print(result)
Answer: C
NEW QUESTION # 117
......
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