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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is one popular programming language used in data science?
💡 Hint: It's known for its simplicity.
Question 2
Easy
Name one library used for data visualization.
💡 Hint: It is often used alongside NumPy.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
Which library would you use for data manipulation in Python?
- Pandas
- Seaborn
- NumPy
💡 Hint: Think about handling data like you would in a spreadsheet.
Question 2
True or False: R is used mainly for visualizations rather than statistical analysis.
- True
- False
💡 Hint: Consider what R is known for.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Critically analyze the choice between using Python and R for a large-scale data analysis project involving both statistical tests and visualizations. What factors will influence your decision?
💡 Hint: Consider both technical capabilities and team skills.
Question 2
Design an interactive data analysis project using Jupyter Notebook or Google Colab that demonstrates the usage of Pandas and Matplotlib. Outline the steps you would take.
💡 Hint: Think about the tasks performed in data analysis and how to present them.
Challenge and get performance evaluation