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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is data privacy?
💡 Hint: Think about how we keep our passwords safe.
Question 2
Easy
What is meant by fairness in machine learning?
💡 Hint: Consider why some models may favor certain groups.
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
What is the primary concern of data privacy?
- A) Protecting data from loss
- B) Protecting sensitive user data
- C) Enhancing data quality
💡 Hint: Consider what personal information needs protection.
Question 2
True or False: Transparency in data science makes automated decisions less trustworthy.
- True
- False
💡 Hint: Think about how much you trust recommendations from clear explanations.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Assess the ethical considerations in deploying an image recognition model that was trained predominantly on images of light-skinned individuals.
💡 Hint: Consider how the diversity in training data impacts outcomes.
Question 2
Develop a plan for how a data science team can improve model transparency when presenting their work to stakeholders.
💡 Hint: Think about the steps needed to make complex models understandable.
Challenge and get performance evaluation