The Data Analytics interdisciplinary minor consists of 20 credit hours typically split between three required foundational courses and two electives chosen from a list representing ten different departments.
The three foundational courses offer students experience in statistics, introduction to programming in R and Python, and exposure to applications of analytics techniques in a variety of real-world settings.
At a minimum, students will need a background in Statistics (MTH-120/ECN-120) for MTH-245. Students pursuing a Data Analytics Minor may substitute CSC-121 for CSC-105 as a prerequisite for CSC-272.
Independent Study, Independent Research, and Directed Independent Study (Courses numbered 501, 502, and 504) may be used as electives with approval of the oversight committee. Likewise, directed summer research experiences (TFA-002) may be considered for use as electives with approval, along with the submission of a substantive research paper to be reviewed by the committee. Faculty-supervised independent study and research offer excellent learning opportunities and should be encouraged when the work is empirical in nature, directly involving data analytics if possible, and congruent with the objectives for the electives above.
For successful completion of the minor, students must give a presentation at Furman Engaged. This may take the form of an oral presentation or a poster, and should detail a significant data analytics project undertaken by the student in the course of their minor studies.
To declare this minor, contact the Data Analytics Minor Chair, Dr. Kevin Hutson, or contact any member of the Data Analytics Minor Oversight Committee to discuss this minor: