Data Science Major (B.S.)

The BS in Data Science is intended for students interested in pursuing advanced degrees and conducting original research in data science. The program places its emphasis on a rigorous introduction to the theoretical mathematical and computational underpinnings of modern data science.

Degree Requirements

All Major, Option and Elective Requirements as indicated.
*Major GPA requirements as indicated.

Major Requirements

Successful completion of the degree program includes earning a minimum of 128 credits, meeting the requirements of the University's Discovery Program, completing all of the 20 required courses in the major as listed below, capstone course, and a minor approved by the advisor.

The following courses or their equivalents must be passed with a grade of C- or better in order to meet the Data Science major requirements: CS 415, CS 416, CS 420, CS 457,and CS 515. 

Students are expected to demonstrate consistent progress towards the satisfaction of the core degree requirements and are allowed two repeats of the aforementioned courses before being removed from the program. This can be a single class repeated twice or two classes repeated once. Students may petition to be reinstated after one year out of the program.

Transfer students may transfer up to a maximum of 32 credits to satisfy major requirements (not counting those courses used to satisfy Discovery requirements).

Sample Degree Plan

This sample degree plan serves as a general guide; students collaborate with their academic advisor to develop a personalized degree plan to meet their academic goals and program requirements.

• Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.
• Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline.
• Communicate effectively in a variety of professional contexts.
• Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
• Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.
• Apply theory, techniques, and tools throughout the data analysis lifecycle and employ the resulting knowledge to satisfy stakeholders’ needs.