DSCI 311: Principles and Techniques of Data Science

In DSCI 311, students will explore intermediate and advanced techniques in data science. This course prepares students to successfully apply computational and statistical techniques to upper-division coursework in data science as well as quantitative, data-driven courses in other domains or subject areas. Topics include managing data with software programs, data cleaning, handling text, dimensionality, principle component analysis, regression, classification and inference. Ethical concerns resulting from use of the techniques in this course will be addressed.

This course is primarily intended for data science majors, with others able to register if prerequisites are met.

Course Syllabus:

Fall 2021 Syllabus

Prerequisites:

DSCI 102, CIS 211, Math 252, Math 342