Practice Core Concept (2.2.1) - Advanced ML Topics & Ethical Considerations (Weeks 14)
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Core Concept

Practice - Core Concept - 2.2.1

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does bias in machine learning refer to?

💡 Hint: Think of examples where AI might treat groups differently.

Question 2 Easy

Name one source of bias in AI.

💡 Hint: Consider the origins of the training data.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main goal of fairness in machine learning?

To maximize accuracy
To ensure equitable treatment among groups
To minimize data usage

💡 Hint: Think about the societal implications of AI decisions.

Question 2

True or False: Explainable AI techniques are only necessary for highly complex models.

True
False

💡 Hint: Consider the importance of clarity in all AI applications.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a framework for ensuring fairness in an AI system used for hiring. What steps would you include?

💡 Hint: Think about each phase from data collection to system deployment.

Challenge 2 Hard

Analyze the potential weaknesses of relying solely on one metric like accuracy to evaluate an AI model.

💡 Hint: Consider what other metrics might provide a better understanding.

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