In this course, we will explore fundamental issues of fairness and bias in machine learning. As predictive models begin making important decisions, from college admission to loan decisions, it becomes paramount to keep models from making unfair predictions. From human bias to dataset awareness, we will explore many aspects of building more ethical models.
About this Course
Skills you will gain
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TOP REVIEWS FROM ARTIFICIAL INTELLIGENCE DATA FAIRNESS AND BIAS
A relatively short and interesting course on data fairness and bias impacting AI models.
Extraodinary course! I've learnt so much! The classes are very informative and dynamic. Didn't feel like studying but rather entertaining myself with hight quality content! Thank you so much!
An excellent reminder that the bias-variance trade-off is not the only trade-off machine learning specialists make.
Really great discussion of algorithms and how their designs make them susceptible to bias.
About the Ethics in the Age of AI Specialization
As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations. In this specialization, we will explore the rise of algorithms, fundamental issues of fairness and bias in machine learning, and basic concepts involved in security and privacy of machine learning projects. We'll finish with a study of 3 projects that will allow you to put your new skills into action.
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