2 courses with the subject DSL, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
An introduction to traditional methods of Data Science with an emphasis on the relevant mathematics, statistics and theory. Topics to include regression, clustering, discriminant analysis, naive Bayes, variable selection, decision trees, and time series.
An introduction to the established Data Science tool kit including clustering, the many faces of regression, random forests, and support vector machines. An optional introduction to neural nets and deep learning. An introduction to the presentation of Data Science results including proper visualization and storytelling. The course consists of three lecture hours and one two-hour laboratory per week.
Source: St Bonaventure University's catalog, linked per course · table learning_unit · CourseShelf publish 61
