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What you'll learn

Understand widely used definitions of fairness and bias

Master principles to follow when training models

Design a healthcare algorithm

Reason about challenging algorithmic fairness dilemmas

Skills you'll gain

ChatGPT

Machine Learning

Software Documentation

Applied Machine Learning

Data Ethics

Artificial Intelligence

Diversity Awareness

Data-Driven Decision-Making

Large Language Modeling

Generative AI

Predictive Analytics

Ethical Standards And Conduct

Law, Regulation, and Compliance

Algorithms

Health Disparities

There are 4 modules in this course

This course is aimed at a broad audience of students in high school or above who are interested in computer science and algorithm design. It will not require you to write code, and relevant computer science concepts will be explained at the beginning of the course. The course is designed to be useful to engineers and data scientists interested in building fair algorithms; policy-makers and managers interested in assessing algorithms for fairness; and all citizens of a society increasingly shaped by algorithmic decision-making.

Designing Algorithms

Documenting Algorithms

Algorithms in the hands of humans