Certificate in Statistical and Computational Data Science
Designed for professionals seeking to enhance their data science skills.
The certificate in statistical and computational data science is designed for professionals seeking to enhance their data science skills or current graduate students who want to round out their degree.
It is a master's-level, five-course (15 credit) certificate that includes graduate-level course requirements from both statistics and computer science.
Graduate matriculated students or post-graduate non-degree students can enroll in the required courses for the Certificate in Statistical and Computational Data Science, as long as they have the prerequisites for the courses and submit the required pre-application.
For students entering the program without strong computer programming skills, we offer a one-credit bridge course: Introduction to Numerical Computing with Python (COMPSCI 590N). This course covers the basics of Python, which is one of the core languages used in data science.
Course Requirements
Bridge Course
- CICS 580: Introduction to Numerical Computing with Python
All students must complete one of the following courses with a grade of "B" or better:
- COMPSCI 589: Machine Learning
- COMPSCI 689: Machine Learning
Students need to complete two or three of the following courses with a grade of "B" or better:
- STAT 535: Statistical Computing (formerly STAT 597A Computational Statistics)
- STAT 597S: Intro to Probability and Math Statistics
- STAT 607: Mathematical Statistics I
- STAT 608: Mathematical Statistics II
- STAT 625: Regression Modeling (formerly STAT 697R)
- STAT 705: Linear Models
Completion of the Certificate
Students who have completed the certificate requirements should submit a certificate eligibility form found here to the Graduate Programs Office. The graduation eligibility deadlines can be found here for obtaining your certificate in the mail. Email the form to kskemer [at] cs [dot] umass [dot] edu (kskemer[at]cs[dot]umass[dot]edu).