Mathematics (B.S.) - Data Science Specialization

Location(s): Brookings Main Campus

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Program Coordinator/Contact

Kurt Cogswell, Department Head
Department of Mathematics and Statistics
Chicoine Architecture, Mathematics and Engineering Hall 209
605-688-6196

Program Information

The Data Science Specialization of the Mathematics degree program provides an outstanding educational experience to students interested in any of the wide range of excellent career or graduate school choices available in the data science. Graduates gain all the mathematical expertise associated with the B.S. in Mathematics degree program while simultaneously building substantial additional expertise in the mathematical, statistical, and computational methods of data science. Graduates are thus prepared for any post-graduation outcome including immediate entry into the professional world or further study in a pursuit of a Master’s degree or a Ph.D. in mathematics, statistics, or data science.

Student Learning Outcomes

Upon completion of the Mathematics major with Data Science Specialization, students will be able to:

Apply concepts and methods from Calculus and Linear Algebra.
Analyze, evaluate, and create mathematically rigorous arguments.
Use contemporary mathematical, statistical, and educational software and technology to create models, analyze data, or explain concepts as appropriate for student’s focus.
Work as part of a team to solve a complex mathematical or statistical problem.
Demonstrate mathematical independence by critically reading, understanding and re-explaining mathematical, statistical, or mathematics pedagogy resources.
Communicate complex mathematical, statistical, or mathematics pedagogical ideas clearly and succinctly both in writing and verbally as appropriate for student’s focus.
Exhibit strength in at least one career-focused or graduate school preparatory area of mathematics or statistics.
Understand and appreciate the contributions to the field of mathematics and statistics by a diverse group of individuals and how the student fits and works in this group.

Academic Requirements

A grade of “C” or above is required in all MATH and STAT courses.

Course Delivery Format

Program courses are delivered on campus, in classroom and laboratory settings, and online.

Requirements for Mathematics Major - Data Science Specialization: 120 Credits

Bachelor of Science

System General Education Requirements

Goal # 1 Written Communication: SGR #1 Electives Credits: 6
Goal #2 Oral Communication: SGR #2 Elective Credits: 3
Goal #3 Social Sciences/Diversity: SGR #3 Electives Credits: 6
Goal #4 Arts and Humanities/Diversity: SGR #4 Electives Credits: 6
Goal #5 Mathematics:
MATH 123 - Calculus I (COM) [SGR #5] Credits: 4
Goal #6 Natural Sciences: SGR #6 Electives Credits: 6

Major Requirements

MATH 125 - Calculus II (COM) [SGR #5] Credits: 4
MATH 198 - The Mathematics Profession (COM) Credits: 1
MATH 225 - Calculus III (COM) [SGR #5] Credits: 4
MATH 230 - Sophomore Seminar Credits: 1
MATH 250 - Introduction to Linear Algebra and Proof Credits: 3
MATH 253 - Logic, Sets, and Proof Credits: 4
MATH 315 - Linear Algebra (COM) Credits: 3
MATH 321 - Differential Equations (COM) Credits: 3
MATH 401 - Senior Capstone Credits: 1-2 (2 credits required)
MATH 425 - Real Analysis I (COM) Credits: 3
STAT 382 - Probability Credits: 3

Select from the following

Select thirty credits from the following. Credits: 30

CSC 250 - Computer Science II (COM) Credits: 3
CSC 300 - Data Structures (COM) Credits: 3
CSC 319 - Parallel Computing (COM) Credits: 3
or CSC 325 - Management Information Systems (COM) Credits: 3
or CSC 447 - Artificial Intelligence (COM) Credits: 3
or CSC 484 - Database Management Systems (COM) Credits: 3
MATH 316 - Discrete Mathematics (COM) Credits: 3
MATH 374 - Scientific Computation I Credits: 3
MATH 415 - Advanced Linear Algebra (COM) Credits: 3
MATH 475 - Operations Research (COM) Credits: 3
STAT 383 - Geospatial Data Analysis Credits: 3
STAT 410 - SAS Programming Credits: 3
STAT 414 - Basic R Programming Credits: 1
STAT 415 - R Programming Credits: 3
STAT 442 - Exploratory and Cloud-Based Data Analysis Credits: 3
STAT 445 - Nonparametric Statistics (COM) Credits: 3
STAT 451 - Predictive Analytics I Credits: 3
STAT 453 - Applied Bayesian Statistics Credits: 3
STAT 460 - Time Series Analysis (COM) Credits: 3
STAT 482 - Mathematical Statistics Credits: 3

Supporting Coursework

CSC 150 - Computer Science I (COM) Credits: 3

Electives

Taken as needed to complete any additional requirements.

Total Required Credits: 120

Summary of Program Requirements

Bachelor of Science
System General Education Requirements	31 Credit Hours
Major Requirements	61 Credit Hours
Supporting Coursework	3 Credit Hours
Electives**	25 Credit Hours

**Taken as needed to complete any additional degree requirements.

Academic Advising Guide Sheet

The goal of the academic advising guide sheets and sample plans of study is to promote undergraduate student success by guiding all students to timely completion of an undergraduate degree. Students are not limited to the course sequence provided for their academic program. Instead, the sample plan of study is one possible path to completing your degree and is meant to be used as a guide for planning purposes in consultation with an academic advisor. The plans also help students prepare for meetings with their academic advisor and track their progress in their selected academic program.