Practice Global Explanations (3.2.2) - Advanced ML Topics & Ethical Considerations (Weeks 14)
Students

Academic Programs

AI-powered learning for grades 8-12, aligned with major curricula

Professional

Professional Courses

Industry-relevant training in Business, Technology, and Design

Games

Interactive Games

Fun games to boost memory, math, typing, and English skills

Global Explanations

Practice - Global Explanations

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

Define bias in the context of machine learning.

💡 Hint: Think about how bias might affect outcomes for specific groups.

Question 2 Easy

What is Explainable AI (XAI)?

💡 Hint: What is the primary goal of XAI?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary concern of bias in machine learning?

Predictive accuracy
Fairness
Computational efficiency

💡 Hint: Consider what bias impacts the most.

Question 2

True or False: Fairness metrics assess only the overall accuracy of a model.

True
False

💡 Hint: Remember, fairness involves looking beyond averages.

Get performance evaluation

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You are tasked with developing a hiring model. Detail how you would approach ensuring fairness from data collection to model deployment.

💡 Hint: Consider the steps in the ML process where bias can arise and how you can address them.

Challenge 2 Hard

Analyze the ethical implications if an AI system used in justice disproportionately impacts minority communities.

💡 Hint: Think about the societal impacts of biased AI systems.

Get performance evaluation

Reference links

Supplementary resources to enhance your learning experience.