DS 400 Data Science Techniques I: 3 semester hours
In this course, we will learn a variety of techniques often used in data analysis. Methods for classification and regression may be considered. Students will continue to develop deeper mathematical skills, programming skills using Python/R, the ability to produce high-quality documents conveying the results of data-based analysis, and more. Topics may include classification with tree-based methods and support vector machines, clustering (such as k-means, hierarchical, and spectral), and dimension-reduction (such as principal component analysis). Issues regarding the ethical use of data will be explored. Prerequisite: DS 301.