Graduate Certificate Program


The Graduate Certificate in Statistics and Machine Learning is designed to formalize the training of students who both contribute to, or make use of, statistics and machine learning as a significant part of their research. In addition, it serves to recognize the accomplishments of graduate students across the University who go beyond the requirements of their own degree programs to acquire additional training in statistics and machine learning.

Enrollment to the Program

The graduate certificate program is open to Princeton students currently enrolled in a Ph.D. or Master’s program at the University. Students may enroll by completing an online application form, linked below.  The application will include a tentative plan and timeline for completing all the course requirements.  Students are encouraged to sign up as soon as possible, preferably in their second or third year, but no later than one semester prior to graduation.

For enrollment, please use this form: Graduate Certificate Enrollment Form

For questions, contact us at

Program of Study

The graduate certificate is comprised of three components: (a) completion of three appropriate graduate courses, (b) a relevant research contribution, and (c) a research seminar. We expect that the core courses can be taken as graduate electives, in partial fulfillment of the various course requirements in home departments, and that the research component will naturally form part of the student's thesis or other research paper.  Participation in the CSML graduate seminar course serves as a venue for reporting current results and discussing the integration of different research approaches to data analysis.  It also serves to build a supportive community of young scholars with shared interests.

Certificate of Proficiency

Each enrolled student who completes the requirements will be awarded a certificate and recognized on the CSML website.


Graduate Certificate Administration

  • Susan Johansen

    • Susan Johansen
      • Academic Program Coordinator
    • Phone: 609-258-2047
    • Email: sjohanse@
    • Office: CSML 209
  • Peter Ramadge

Participating Faculty