Practice - Advanced ML Topics & Ethical Considerations
Practice Questions
Test your understanding with targeted questions
What is bias in the context of machine learning?
💡 Hint: Think about how data reflects societal stereotypes.
Name one method used to ensure fairness in ML models.
💡 Hint: Consider how different demographic groups are treated by AI.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What is the primary purpose of Explainable AI?
💡 Hint: Think about how users benefit from understanding AI decisions.
True or False: Bias is always intentional in machine learning.
💡 Hint: Consider how societal biases can surface in technology.
Get performance evaluation
Challenge Problems
Push your limits with advanced challenges
Design a machine learning approach to address bias in credit scoring models. Describe interventions across each stage of the machine learning lifecycle.
💡 Hint: Think about the sources of bias at different stages of the ML process.
Evaluate the ethical implications of using AI in healthcare diagnostics where bias might affect treatment recommendations. Propose a framework for addressing these biases.
💡 Hint: Focus on equitable access to healthcare as a primary concern.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.