If you have questions about the undergraduate Certificate in Data Science, please check the FAQ we are developing. If you do not find your answer there, you may consult the Certificate Coordinator, Winston Lin (firstname.lastname@example.org).
Description of the certificate:
The certificate in Data Science is available to the Class of 2020 and beyond. It requires 5 course credits:
- Probability and Statistical Theory: one of S&DS 238, 240, 241, 242. Advanced students may substitute S&DS 351 or 364.
- Statistical methodology and data analysis: two of S&DS 230, 242, 312, 361, 363. Econ 136 may be substituted for S&DS 242.
- Computation & Machine Learning: one from S&DS 262, 355, 365, CPSC 223, 477. CPSC 323 may be substituted for CPSC 223.
- A credit of data analysis in a discipline area. This can be either:
- Two of the 1⁄2-credit seminars that accompany S&DS 123 (presently S&DS 170, 171 and 172)
- One of the “Data Science in a Discipline Area” courses approved for the data science certificate, which are listed below.
Students are required to earn at least B- in each course counted towards the certificate, and no course may be used to fulfill more than one requirement of the certificate. No course may be counted towards both the certificate and a major.
Students are encouraged to take an introductory course, such as one of S&DS 100, 10X, 123 or 220, before taking courses for the certificate. This is described as the “prerequisite” in the YCPS.
The “Data Science in a Discipline Area” courses for the data science certificate are courses that expose students to how data are gathered and used within a discipline outside of S&DS. The courses currently approved for this purpose are:
- PSYC 235 (Research Methods in Psychology)
- PSYC 258 (Computational Methods in Human Neuroscience)
- PLSC 454 (Data Science for Politics and Policy)
- ANTH 376 (Observing and Measuring Behavior)
- EVST 362 (Observing Earth from Space)
- GLBL 191 (Research Design and Survey Analysis)
- GLBL 195/PLSC 341 (Logic of Randomized Experiments in Political Science)
- LING 227 (Language and Computation I)
- LING 229 (Language and Computation II)
- LING 234 (Quantitative Linguistics using Corpora)
- LING 380 (Neural Networks and Language)
- ASTR 356 (Astrostatistics and Data Mining)
- MB&B 452 / MCDB 452 / S&DS 352 (Biomedical Data Science, Mining and Modeling)
The department is planning to expand the list of courses above to more disciplines.
Restrictions, suggestions, and caveats:
- The department recommends that most students take a 100-level course, followed by 238, 230 and one of 361 or 363. Students who take 220 should NOT take 230, and should instead take 361 and then another course in Data Analysis (363 or 312).
- Students considering majoring in Statistics and Data Science should be very careful about which courses they take. Some courses that count towards the certificate (right now 240 and 355) do NOT count towards the major.
- Students may not count courses toward both their major and the certificate. If a course in the certificate is required by a student’s major, then the student should substitute a different course in the certificate.
- S&DS Majors may not pursue the Data Science certificate.