Practice - Facilitating Debugging, Improvement, and Auditing
Practice Questions
Test your understanding with targeted questions
What is bias in machine learning?
💡 Hint: Think about how previous data influences current decisions.
Name a technique used in Explainable AI.
💡 Hint: It starts with a letter 'L' and stands for Local Interpretable Model-agnostic Explanations.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the primary focus of Explainable AI (XAI)?
💡 Hint: Consider what 'explainable' implies.
True or False: Transparency is not critical for AI systems.
💡 Hint: Think about why users need to understand AI.
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Challenge Problems
Push your limits with advanced challenges
Your organization deploys a machine learning model for recruitment that exhibits bias against underrepresented groups. Propose a systematic approach to identify and mitigate this bias throughout the model's lifecycle.
💡 Hint: Consider a full lifecycle approach—starting from data collection to monitoring.
You are developing an AI system to provide medical diagnoses. Given potential ethical implications, outline how you would ensure accountability and transparency in your system.
💡 Hint: Think about the roles different people play at each stage.
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Reference links
Supplementary resources to enhance your learning experience.