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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is meant by 'data quality' in the context of AI?
💡 Hint: Think about the importance of data in making predictions.
Question 2
Easy
What are black-box models?
💡 Hint: Consider what transparency means in decision-making.
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
Why is data quality important in AI models?
- It increases costs
- It decreases efficiency
- It affects predictions
💡 Hint: Think about what happens when data is not reliable.
Question 2
True or False: Black box models are transparent and easily understood.
- True
- False
💡 Hint: Consider the meaning of transparency in AI.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Propose a comprehensive strategy for ensuring data quality in an upcoming infrastructure project that employs AI. Include steps for data sourcing, validation, and bias mitigation.
💡 Hint: Think about how you can involve different roles for a better data strategy.
Question 2
Develop a framework for addressing ethical and legal concerns related to AI use in civil engineering projects, considering accountability and privacy issues.
💡 Hint: Consider what organizations are currently doing to address these issues.
Challenge and get performance evaluation