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, pending revision 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)

 

Course #Course Name
01:198:439 Introduction to Data Science (and 198:310 capstone)
01:220:322 Econometrics (and 220:323 capstone)
01:447:302 Quantitative Biology and Bioinformatics (and 198:310 capstone)
01:447:303 Computational Genetics of Big Data (and 198:310 capstone)
01:450:320 Spatial Data Analysis (and 198:310 capstone)
01:450:321 Geographic Information Systems (and 198:310 capstone)
01:450:330 Geographical Research Methods (and 198:310 capstone)
01:640:350 Linear Algebra (and 198:310 capstone)
01:640:477 Mathematical Theory of Probability (and 198:310 capstone)
01:640:478 Introduction to Stochastic Processes (and 198:310 capstone)
01:640:481 Mathematical Theory of Statistics (and 198:310 capstone)
01:750:345 Computational Astrophysics (and 198:310 capstone)
01:790:391 Data Science for Political Science (and 198:310 capstone)
01:830:400 Advanced Statistical Methods in Psychology (and 198:310 capstone)
01:830:403 Programming for Behavioral Scientists (and 198:310 capstone)
04:547:321 Information Visualization (and 198:310 capstone)
01:960:365 Bayesian Data Analysis (and 198:310 capstone)
01:960:463 Regression Methods (and 198:310 capstone)
01:960:486 Computing and Graphics in Applied Statistics (and 198:310 capstone)
- Other, to be determined

 

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)