Undergraduate Certificate

Open to ALL students! The goals of the Data Science Certificate program are achieved by completing three foundational courses followed by an advanced domain-specific course and a mini-capstone course.

Please use this form to track your progress. Upon completion, please submit completed form to This email address is being protected from spambots. You need JavaScript enabled to view it.

Students must take 4 courses (14 to 16 credits) which include a 1-credit recitation (mini-capstone) for skills demonstration for the successful completion of the Certificate in Data Science.

Students must maintain a G.P.A. of 2.0 in the courses applied to the certificate. No courses with grade D can be counted toward the certificate.

 

#NumberTitlePrerequisites
I 01:198:142/ 01:960:142 Data 101 Some math knowledge
II 01:960:291 Statistical inference for data science 01:198:142/ 01:960:142
III 01:198:210 Data management for data science 01:198:142/ 01:198:111
01:960:295 Data management and wrangling with R 01:198:142/ 01:960:142
04:547:221 Fundamentals of big data curation & management 01:198:142/ 01:960:142
IV xx:xxx:xxx Domain Course Departmental prerequisites
IV+ 01:198:310 1 credit capstone - default option I, II, and III
01:220:323 1 credit capstone for economics I, II, and III

 

IV. Domain classes (check department for prerequisites)

 

RU-NB School Department Course # Title Capstone 
SAS (01) COMPUTER SCIENCE (198)  439 Introduction to Data Science  default, 198:310 
SAS (01)  ECONOMICS (220) 322 Econometrics 01:220:323, to be taken after, not concurrent with 322
SAS (01) ENGLISH (359) 463 Regression Methods default, 198:310 
SAS (01) GENETICS (447) 303 Computational Genetics for Big Data default, 198:310
SAS (01)  GEOGRAPHY (450) 320 Spatial Data Analysis  default, 198:310
SAS (01)  GEOGRAPHY (450) 321 Geographic Information Systems default, 198:310
SAS (01) GEOGRAPHY (450) 330 Geographical Research Methods default, 198:310
SAS (01) PHYSICS (750) 345 Computational Astrophysics default, 198:310
SAS (01) POLITICAL SCIENCE (790) 391 Data Science for Political Science default, 198:310
SAS (01) SOCIOLOGY (920) 360 Computational Social Science default, 198:310
SAS (01) STATISTICS (960) 365 Bayesian Data Analysis default, 198:310
SAS (01) STATISTICS (960) 463 Regression Methods default, 198:310
SAS (01) STATISTICS (960) 486 Computing and Graphics in Applied Statistics default, 198:310
SCI (04) DIGITAL COMMUNICATION, INFORMATION, AND MEDIA (189) 220 Data in Context default, 198:310
SCI (04) INFORMATION TECHNOLOGY AND INFORMATICS (547) 321 Information Visualization

default, 198:310


Data Science UG Certificate Course Planner/Navigator 

 

CompletionSpring Semester startFall Semester Start
In 3 semesters Spring: Data 101 (CS142) Fall: Data 101(CS142)
Fall: Stats inference (Stats291) and Data Management class (CS210/Stats295) Spring: Data Management class (CS210/Stats295) and Domain class(choose)
Next Spring: Domain class(choose) plus Capstone(CS310) Next Fall: Stats inference (Stats291) plus Capstone(CS310)/(Econ323)
In 4 semesters Spring: Data 101(CS142) Fall: Data 101(CS142)
Fall: Stats inference (Stats291) Spring: Data Management class (CS210/Stats295)
Next Spring: Data Management class (CS210/Stats295) Next Fall: Stats inference (Stats291)
Next Fall: Domain class(choose) plus Capstone(CS310)/(Econ323) Next Spring: Domain class(choose) plus Capstone(CS310)