Dec 05, 2025

2025-2026 Undergraduate Catalog

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2025-2026 Undergraduate Catalog

Data Science, B.S.

Program Learning Outcomes for B.S. in Data Science.

Students pursuing the B.S. in Data Science are required to:

Earn an overall GPA of 2.500 for all required lower-division major courses.
Earn an overall GPA of 2.000 for all required major courses.
Complete all courses in the major for a letter grade of “C-” or higher, except those where the default grading option is P/NP.
Complete a minimum of 21 credits from upper division courses in the major.

Majors are required to enroll in FFC 100B - First Year Foundations: Grand Challenges in Science and Engineering to satisfy their General Education requirement.

Grand Challenges Initiative (3 credits)

GCI 150 - Grand Challenges in Science and Engineering I 1 credit
GCI 200 - Grand Challenges in Science and Engineering II 1 credit
GCI 250 - Grand Challenges in Science and Engineering III 1 credit

lower-division requirements (27 credits)

ENGR 101 - Foundations of Design and Fabrication 3 credits
MATH 110 - Single Variable Calculus I 3 credits
ECON 200 - Principles of Microeconomics 3 credits
MATH 203 - Introduction to Statistics 3 credits
MGSC 220 - Foundations of Business Analytics 3 credits
CPSC 230 - Computer Science I 3 credits
CPSC 231 - Computer Science II 3 credits
CPSC 285 - Social and Ethical Issues in Computing 3 credits
CPSC 293 - Mathematical Foundations of Machine Learning 3 credits

colloquium requirement (5 credits)

Students must complete five 1-credit sections of CPSC 298 - Computer Science Colloquium .

upper-division requirements (30 credits)

MGSC 310 - Statistical Models in Business Analytics 3 credits
CPSC 349 - Human Factors 3 credits
CPSC 350 - Data Structures and Algorithms 3 credits
CPSC 353 - Data Communications and Computer Networks 3 credits
CPSC 355 - Human Computer Interaction 3 credits
CPSC 390 - Artificial Intelligence 3 credits
CPSC 392 - Introduction to Data Science 3 credits
CPSC 393 - Machine Learning 3 credits
CPSC 408 - Database Management 3 credits
MGSC 410 - Applied Business Analytics 3 credits

electives (9 credits)

three of the following

MATH 303 - Biostatistics 3 credits
ENV 310 - Geographic Information Systems, Lecture and Laboratory 4 credits
CPSC 358 - Assistive Technology 3 credits
CPSC 359 - Computer-Supported Cooperative Work 3 credits
MATH 360 - Probability Theory 3 credits
MATH 361 - Mathematical Statistics 3 credits
ISP 363 - Cybersecurity 1 3 credits
MGSC 406 - Advanced Experimental Design and Statistics 3 credits
CPSC 430 - Computational Economics 4 credits
CPSC 435 - BioMedical Informatics 3 credits
CPSC 445 - High Performance Computing 3 credits
ECON 452 - Econometrics 3 credits
CPSC 458 - Web Engineering 3 credits
MGSC 496 - Special Topics in Management Science 3 credits (Applied Analytics and Decision Making)

Professional Portfolio (1 credit)

Students must complete a 1-credit section of ENGR 397 - Engineering Portfolio Design .

total credits 75

Data Science, B.S. Suggested 4-year Plan

Data Science, B.S. Suggested 4-Year Plan