Data Science - Minor

Data science is a multidisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data.

This minor provides students with an introduction to the core concepts and skills of data science in computing, statistics and information science to complement existing majors in CMCI fields, in the social sciences and in the arts and humanities.

The program is specifically designed as an add-on to existing quantitative methods courses and sequences in the social sciences. Students in such degree programs who wish to add data science experience and credentials to their course of study can complete the minor without additional course prerequisites. For this reason, some aspects of the curriculum (particularly the quantitative methods area) are quite flexible, allowing students to acquire this background through subject-specific study in a variety of disciplines.

Required Courses and Credits

The minor is divided into three areas: computing, quantitative methods, and electives. Computing courses cover basic programming and data structures with an emphasis on the Python programming language. Because of the variation in credit hours associated with quantitative methods courses, the total hours for the minor vary between 19–22. Students may apply no more than six credit hours of transfer work, including three hours of upper-division credit.

Information Science majors may not receive an Information Science minor nor a Data Science minor. Students may not receive both the Information Science minor and the Data Science minor.

All coursework applied to the minor must be completed with a grade of C- or better (no pass/fail work may be applied). The GPA for all coursework attempted in the minor department must be equal to 2.00 (C) or higher.

Aside from course prerequisites for the courses listed below, there are no other prerequisites for the minor.