Data Analysis

Catalog description

Data analysis using simulation, machine learning algorithms: logistic regression, Naive Bayes, decision trees, k-means, k-nearest neighbors, and dimension reduction (principal component analysis). Students will learn how to test and validate models as well as format and display data. A data analysis project will be completed. Prerequisite: grade of C or higher in 230.