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.

Students must take 4 courses (14 to 16 credits) which include a 1-credit 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.

Certificate Completion Form

Congratulations on completing the Data Science Certificate! We are thrilled to recognize your hard work and dedication. To finalize the certification process, please complete this form which is the final step in confirming your accomplishment. We celebrate your success and look forward to acknowledging your journey in data science (note: please turn the mobile-friendly feature off when accessing the form on your phone):

DS Certificate form

 Please note that The Certificate Completion Forms will only be processed in January and May. January graduates can submit their forms starting in December, while May graduates can submit them starting in April.

 

Course Requirements

Students must take 4 courses (14 to 16 credits) in addition to a 1-credit recitation (mini-capstone) for skills demonstration to successfully complete 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 a grade of D can be counted toward the certificate.

Please note:

The remaining classes have to be completed BEFORE the Capstone project. No class (except the domain course) can be taken in parallel with the Capstone.
For remaining classes - they may be taken in parallel if prereqs are satisfied and/or with permission of program directors.

● Data 101: Data Literacy (01:198:142/01:960:142) must be taken, (no waivers)

  • Statistical Inference for Data Science (01:960:291)
  • [ As of Dec. 2023, the 01:960:291. Statistical Inference for Data Science requirement has been expanded to include any of the following: 01:960:212 Statistics II, OR 01:960:384 Intermediate Statistical Analysis, OR 33:136:385 Statistical Methods in Business.]
  • Data Management: choose one of the following:
    • Data Management for Data Science (01:198:210), or
    • Data Management and wrangling with R (01:960:295), or
    • Fundamentals of data curation and management (04:547:221)
 

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) 207 Data and Culture 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 Applied Statistical Learning  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

SEBS (11)  BIOTECHNOLOGY (126) 485 Functional Genomics default, 198:310
SOE (14) ELECTRICAL AND COMPUTER ENGINEERING (332) 443 Machine Learning for Engineers default, 198:310
  •  1 credit Data Science Capstone Project (01:198:310)
  • 1 credit Data Science and Econometrics (01:220:323)

 

View Data Science Certificate Pathway

 

#NumberTitlePrerequisites
I 01:198:142/ 01:960:142 Data 101: Data Literacy Some math knowledge
II 01:960:291 or 01:960:212 Statistical inference for data science or Statistics II 01:198:142/ 01:960:142
III 01:198:210 Data management for data science, or 01:198:142/ 01:198:111
01:960:295 Data management and wrangling with R, or 01:198:142/ 01:960:142
04:547:221 Fundamentals of data curation & management 01:198:142/ 01:960:142
IV xx:xxx:xxx Domain Course (select one from list below) Departmental prerequisites
IV+ 01:198:310 1 credit Data Science Capstone Project - default option, or I, II, and III
01:220:323 1 credit capstone Data Science and Econometrics I, II, and III