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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is bias in training data?
💡 Hint: Consider how historical biases might persist in data.
Question 2
Easy
Why is model explainability important?
💡 Hint: Think of situations where understanding AI decisions is critical.
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 can bias in training data lead to?
- Fair outcomes
- Unfair outcomes
- Balanced decisions
💡 Hint: Remember how historical data might affect future decisions.
Question 2
Is model explainability important for trust?
- True
- False
💡 Hint: Consider the consequences of not understanding decisions.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Discuss how a biased AI model in healthcare could lead to potential harm.
💡 Hint: Consider scenarios involving misdiagnoses or unequal healthcare access.
Question 2
Evaluate the efforts several tech companies have made to reduce their carbon footprints in AI.
💡 Hint: Research recent sustainability reports from major tech firms.
Challenge and get performance evaluation