Foundations of Data Science Introduction to the life cycle of data starting from data collection to cleaning, management, storage, sorting, provenance, visualization, and analysis. A rigorous overview of methods for text mining, image processing, linear models, and scientific computing. Core concepts in supervised and unsupervised analytics, dimensionality reduction, and data visualization will be explored in depth. Credit Hours: 4 Prerequisites: Permission of department Semester Offered: Fall Level: Graduate
