Pursue a Data Science Certificate
Pursue a Data Science Certificate
If you’re a Yale undergraduate interested in data–how it’s collected, analyzed, and applied—consider pursuing a certificate in Data Science. For more on the launch of the certificate, visit the announcement in Yale Daily News.
The certificate in Data Science is available to the Class of 2020 and beyond. It requires 5 course credits from the following areas:
Probability and Statistical Theory: one of S&DS 238, 240, 241, 242. Advanced students may substitute with S&DS 351 or 364 or EENG 431.
Statistical Methodology and Data Analysis: two of S&DS 230, 242, 312, 361, 363. Econ 136 may be substituted for S&DS 242.
Computation and 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 course can be either:
- S&DS 171 OR 172 if taken in Spring 2020 or later. (For pre-2020 offerings, the equivalent would be two of the 1⁄2-credit seminars-S&DS 170, 171 and 172-that accompanied S&DS 123.)
- One of the “Data Science in a Discipline Area” courses listed below that have been approved for the data science certificate.
Students are required to earn at least a B- in each course counted towards the certificate (or a Pass for courses taken in Spring 2020). No course may be used to fulfill more than one requirement of the certificate. Also, no course may be counted towards both the certificate and a major.
Students are encouraged to take an introductory course, such as S&DS 100, 10X, 123, or 220 (or an introductory data analysis course in another department), before taking courses for the certificate.
The qualifying “Data Science in a Discipline Area” courses expose students to how data are gathered and used within a discipline outside of S&DS. The courses currently approved for this purpose are:
- ANTH 376, Observing and Measuring Behavior
- ASTR 356, Astrostatistics and Data Mining
- ECON 438, Applied Econometrics: Politics, Sports, Microeconomics
- ECON 439, Applied Econometrics: Macroeconomic and Finance Forecasting
- EVST 362, Observing Earth from Space
- GLBL 191, Research Design and Survey Analysis
- LING 227, Language and Computation I
- LING 229, Language and Computation II
- LING 234, Quantitative Linguistics using Corpora
- LING 380, Neural Networks and Language
- MB&B 452 / MCDB 452 / S&DS 352, Biomedical Data Science, Mining and Modeling
- PLSC 340 / S&DS 315, Measuring Impact and Opinion Change
- PLSC 341 / GLBL 195, Logic of Randomized Experiments in Political Science
- PLSC 454, Data Science for Politics and Policy
- PSYC 235, Research Methods in Psychology
- PSYC 258 / NSCI 258, Computational Methods in Human Neuroscience
- PSYC 438 / NSCI 441, Computational Models of Human Behavior
- S&DS 171, YData: Text Data Science: An Introduction (if taken in Spring 2020 or later)
- S&DS 172, YData: Data Science for Political Campaigns (if taken in Spring 2020 or later)
- S&DS 173, YData: Analysis of Baseball Data (if taken in Spring 2020 or later).
The department is planning to expand the list of courses above to more disciplines.
Suggestions and Caveats
The department recommends that most students take a 100-level course, followed by 238 or 240, 230, and one of 361 or 363.
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.
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. S&DS majors may not pursue the Data Science certificate.
For more information and to register, visit the S&DS webpage. If you have questions about the certificate, please check the FAQ page. If you do not find your answer there, reach out to the Certificate Coordinator, Winston Lin.
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