Data Science

and The fundamental techniques related to data acquisition, data statistical modeling, experimental design, feature engineering, and modeling with machine learning. It explores the problems that arise in different ways of performing those tasks, the fairness and bias of machine learning models, data visualizations, and user interfaces. In addition, covers anonymization and deanonymization, conceptions of privacy from a number of perspectives