Foundations of Data Science

Catalog description

Basic programming and statistical concepts. Includes programming for data cleansing, manipulation, visualization, and statistical computation for intelligence gathering. Students will apply common built-in language functions for analysis of real-world datasets, including global and local economic data, commercial business, document collections, and social networks. Also delves into machine learning and data driven decision-making using statistical concepts like hypothesis testing, confidence intervals via bootstrapping, regression and inference for regression, and predictive modeling. Students will also learn about social issues surrounding data privacy and ownership. 54.00 hours lecture and 18.00 hours laboratory. (Same as CIS-70A) (Letter grade or Pass/No Pass option)