STATS 3DS3 - Introduction to Data Science Theory

3 unit(s)

An introduction to data science theory is provided with some focus on analytics. Topics covered include an introduction to R and other appropriate computational platforms, data types, data manipulation, data frames, data visualization, data reporting, statistical/machine learning, classification, clustering, cross-validation, classification and regression trees, gradient boosting, ridge regression, LASSO, and generalized additive models. Familiarity with some computer package, e.g. SAS, Python or MatLab is required. This course includes a scientific communication component.
Two lectures, one lab; one term
Prerequisite(s): One of ECON 3EE3, PNB 3XE3, SFWRTECH 4DA3, STATS 3A03