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| Section | Weight | Objectives |
|---|---|---|
| SQL and Database Integration | 10% | - Python-database connectivity
|
| Data Exploration and Statistical Analysis | 25% | - Exploratory data analysis
|
| Data Acquisition and Preprocessing | 30% | - Data cleaning and validation
|
| Data Modeling and Machine Learning Basics | 20% | - Supervised learning fundamentals
|
| Data Visualization and Communication | 15% | - Visualization with Matplotlib and Seaborn
|
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NEW QUESTION # 22
Which metric is most appropriate for evaluating the accuracy of a classification model?
Answer: A
NEW QUESTION # 23
Which method is typically used in Pandas to check if a column contains only values within an expected range?
Answer: C
NEW QUESTION # 24
When analyzing a dataset, which of the following functions would best help detect skewness or asymmetry in the data distribution?
Answer: D
NEW QUESTION # 25
Which technique is considered a primary defense against SQL injection when executing database queries from Python?
Answer: C
NEW QUESTION # 26
When analyzing a dataset of customer ages, you calculate the mean, median, and mode. What does it indicate if all three values are approximately equal?
Answer: B
NEW QUESTION # 27
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