DSCI 407 - Predictive Analytics for Business

Predictive analytics relates to extracting patterns, associations, and trends from data (commonly known as ‘data mining’). This course covers two main areas in predictive analytics: methods of regression for predicting quantitative variables and methods of classification for predicting qualitative variables. It also covers some multivariate statistical methods such as principal component analysis, cluster analysis, and association rules. This course aims to provide a theoretical and practical overview of recently-developed methods such as generalized additive models, bagging and boosting, shrinkage methods, support vector machines, and resampling methods as well as classical statistical learning methods.

Prerequisites & Notes: DSCI 305.
Credits: 4
Grade Mode: Letter