DATA 374 - Classification Models

3 Credits
This course provides the foundational knowledge to use classification models to create business insights and other real-world problems. It teaches a systematic approach for building classification models from an input data set. Examples include decision tree classifiers, logistic regression, KNN, support vector machines, and naıve Bayes classifiers. The course design purposely makes it easy to learn commonly used classification algorithms and how to use those algorithms to solve business problems. Upon completing this course, students will be able to clearly define a classification problem, extract and prepare data, explore data using univariate and bivariate visualization, and build and evaluate classification models using five basic and advanced algorithms.

Prerequisite(s): DATA 275 DATA 342