Algorithmic fairness is one of the most important topics in the last decade of data science, and has attracted significant attention from industry and academia. As part of the Data Science for the Common Good summer program, students investigated potential issues in data-driven systems that contribute to algorithmic fairness, in order to help data practitioners understand and identify these issues in their data and the related machine learning tasks.