Certificate in Data Science
The Certificate in Data Science option allows undergraduate students to receive recognition for completing coursework that provides an understanding of the discipline of data science including exposure to data structures and data sources, statistical principles, computing and analytics, data management, and data science applications. Courses on the Approved List under Interdisciplinary Data Science include subject matter courses and courses that require substantial interpretation of data and report writing. Students completing the Certificate will be presented with an official certificate document and will be free to use this credential on a CV, resume or application for advanced study.
Data Science Course Requirements
For completion of the Certificate in Data Science, students must complete at least four courses (3-4 credit hours each) for a total of 12-16 credit hours of coursework from the Approved List of Courses below. Two 3-4 credit hour courses are required from Group 1 on the Approved List below. One 3-4 credit hour course is required from each of Groups 2 and 3 on the Approved List.
All courses applied to the certificate may also be counted toward the requirements of the student's declared major. Students are not guaranteed a seat in a course required by the certificate, but are welcome to enroll in courses where seats remain available after any restriction that may have been placed has been removed. No course substitutions will be approved.
1. Fundamentals of data, sampling, statistics, and machine learning (Choose 2 courses)
- STAT 200: Statistical Analysis, credit: 3 hours
- STAT 212: Biostatistics, credit: 3 hours
- (Credit is not given for both STAT 200 and STAT 212)
- STAT 420: Methods of Applied Statistics, credit: 3 hours
- STAT 432: Basics of Statistical Learning, credit: 3 hours (new course)
- STAT 448: Advanced Data Analysis, credit: 4 hours
2. Data structures, programming and visualization (Choose 1 course)
- MATH 225: Introductory Matrix Theory, credit 3 hours
- MATH 415: Applied Linear Algebra, credit 3 or 4 hours
- (Credit is not given for both MATH 225 and MATH 415)
- STAT 385: Statistics Programming Methods, credit: 3 hours
- STAT 428: Statistical Computing, credit: 3 hours
- STAT 440: Statistical Data Management, credit: 3 hours
- STAT 480: Data Science Foundations, credit: 3 hours
3. Interdisciplinary data science (Choose 1 course)
- ECON 471: Intro to Applied Econometrics, credit: 3 hours
- GEOG 371: Spatial Analysis, credit: 4 hours
- GEOG 379: Intro to GIS Systems, credit: 3 hours
- LING 402: Tools & Tech Spch & Lang Proc, credit: 3 Hours.
- LING 406: Intro to Computational Ling, credit: 3 or 4 hours
- MCB 432: Computing in Molecular Biology, credit: 3 Hours
- PS 230: Intro to Pol Research, credit: 3 hours
- SOC 380: Social Research Methods, credit: 4 hours
- SOC 488: Demographic Methods, credit: 3 hours
- STAT 443: Professional Statistics, credit: 3 hours
The certificate is administered by the Department of Statistics undergraduate advising team. Contact the departmental undergraduate office or data science certificate advisor for more information.