Grounded in the liberal arts, students will learn how data can be used to understand the world through multiple disciplinary lenses (e.g., business, economics, history, music, political science, et cetera). Students will learn introductory data organization and visualization skills. Students will pose interesting questions about real-world data, learn the computational tools needed to organize and visualize data related to the question, draw meaningful conclusions from such analyses, and communicate their findings. One college-level statistics course recommended

Reading and discussion in data analytics, moderated by a faculty member in data analytics or major with a specific data analytics problem. Interested faculty and students in other areas are welcome to participate as well. Each section of this course is typically devoted to a single work, but occasionally a group of smaller works by a single author may be selected. S/U grading only. May be repeated for credit.

This course provides students an opportunity to gain greater proficiency in computer programming, data management, and visualization. The emphasis will be on leveraging the skills acquired in earlier courses and providing students with the opportunity to more fully develop their abilities to organize, visualize, and analyze real-world data as well as communicate findings.

This course will provide an integrative experience where students use computing, statistics, and disciplinary skills to explore a particular data-related project. The final project should demonstrate satisfaction of the learning goals of the minor. Students complete a standalone activity distinct from their major under the supervision of a faculty member outside of their major.

Content varies from semester to semester. Course would apply existing technological knowledge to the study of humanities, social sciences, fine arts, or other disciplinary areas or could be focused on the development of new technological skills and applications. May be repeated for credit when topics vary. Additional prerequisites possible depending on the topic.