Mathematics : Applied Data Science Option, BS

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This option is designed to allow students to double major in data science and another bachelor’s level degree program that would benefit from a data focused curriculum.

General Education Shared Core (36 credit hours)

Core Requirements (12 credit hrs) See list …

English composition (6 hrs)
Oral communication (3 hrs)
Mathematics (3 hrs)

General Requirements (24 credit hrs)

Humanities/Fine Arts (9 hrs); at least 3 hrs Humanities and 3 hrs Fine Arts
Social Sciences (9 hrs); in at least two different disciplines
Natural Sciences (6 hrs); 3 hrs Physical Science and 3 hrs Life Sciences, one of which must be a lab course

Suggestions for General Education

CMAT 2030 is recommended for oral communication.
The mathematics requirement is embedded in the major requirement.
Economics 1010 and/or Economics 1020 are recommended for the Social Science requirement.
Physics 2110 is recommended for the physical science course.
The above recommendations are not mandatory; other general education choices from the approved list are accepted.

College of Arts and Sciences General Education Requirements (3 credit hrs)

General Education
One course in a World Language (3 hrs)
One general education or major course carrying the diversity designation (embedded)

Specific Requirements

Required Courses (40 credits)

The Bachelor of Science in Mathematics with the Applied Data Science Option is only for Double Majors. This 120-credit hour program includes 40 hours of required courses and 41 hours of electives, designed for students whose primary major lies outside mathematics. This option provides a robust secondary major in mathematics focused on data science, while ensuring flexibility to accommodate the student’s primary area of study. The degree plan of the required courses offers a strategic injection of content that is carefully sequenced to be integrated into the student’s overall degree plan, enabling them to acquire critical mathematical and computational competencies essential for success in data-intensive fields. Electives, especially from the primary major, allow a more realistic pathway for timely degree completion.

The double major delivers foundational training in data engineering, statistics, linear algebra, and modern computing, with opportunities for interdisciplinary customization through advisor- approved electives. The 41 hours of electives, some of which can be double counted for both majors, can be chosen from the student’s primary major, mathematics, computer science, or other disciplines. All electives applied to the mathematics degree must be chosen with the express approval of the Mathematics Advisor and all electives, which are not in mathematics, must be data-driven in nature. Furthermore, the selected electives should augment the required courses to form a coherent body of coursework that supports the development of a meaningful pathway in data science tailored to the student’s interests and career goals.

MATH 1050 - Introduction to Data Engineering Credit Hours: 3
CPTR 1100 - Introduction to C++ Programming Credit Hours: 3
MATH 1410 - Calculus I Credit Hours: 4 OR
MATH 1415 - Calc Life Sci I Credit Hours: 4
MATH 1420 - Calculus II Credit Hours: 4
MATH 1600 - Basic Prob/Statis I Credit Hours: 3
MATH 2200 - Linear Algebra Credit Hours: 3
CPTR 2320 - Introduction to Applied Machine Learning Credit Hours: 3
MATH 3000 - Design Thinking Credit Hours: 2
MATH 3650 - Introduction to Statistical Modeling Credit Hours: 3
MATH 3660 - Introduction to Bayesian Statistics Credit Hours: 03
CPTR 4600 - Intro Database Systm Credit Hours: 3
MATH 4940 - Mathematics Seminar Credit Hours: 3
3 credits of 4000 level coursework approved by departmental advisor OR a Data Mining class Credits / Units: 3

Elective Courses

41 Credit Hours of Elective Courses