Graduate Certificate Program

Average Phan work

The visual image is an excerpt from the research work of Average Phan, a doctoral student, who is studying how bacteria communicate with each other. He is using data science tools to model this communication.

Overview

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

Enrollment to the Program

This certificate program is open to Princeton University students currently enrolled in a Ph.D. or master’s program at the University. Students must enroll by completing an online application form on the CSML website. 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, and no later than one semester prior to graduation.  Because Ph.D. students who have entered Dissertation Completion Enrollment (DCE) status are not eligible to enroll in courses, Ph.D. students must enroll in the CSML graduate certificate program in time to complete the course requirements while they are still in their regular degree program length.

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

For questions, contact us at [email protected]

Program of Study

For students enrolled in a graduate degree program with a thesis or dissertation requirement, the 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 item (b) will naturally form as part of the student’s thesis or dissertation. For non-thesis master’s students, item (b) is replaced by a research paper and a technical presentation. The certificate will appear on a student’s official transcript after all requirements for the certificate have been fulfilled and a graduate degree has been awarded. Students who earn the certificate will also be recognized on the CSML website.

Certificate of Proficiency

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


 

Graduate Certificate Administration

Susan Johansen
Academic Program Coordinator
Center for Statistics & Machine Learning
Office Phone
Office
CSML 209
Peter Ramadge
Director, Center for Statistics & Machine Learning
Electrical & Computer Engineering
Office
CSML 204

Participating Faculty

Sigrid Adriaenssens
Civil & Environmental Engineering
Amir Ali Ahmadi
Operations Research & Financial Engineering
Christine Allen-Blanchette
Mechanical & Aerospace Engineering/Center for Statistics & Machine Learning
Sanjeev Arora
Computer Science
Jonathan Cohen
Psychology/Princeton Neuroscience Institute
Adji Bousso Dieng
Computer Science
Peter Elmer
Physics
Jianqing Fan
Operations Research & Financial Engineering
Jaime Fernández Fisac
Electrical & Computer Engineering
Filiz Garip
Sociology
Boris Hanin
Operations Research & Financial Engineering
Elad Hazan
Computer Science
Bo Honoré
Economics
Niraj Jha
Electrical & Computer Engineering
Jason Klusowski
Operations Research & Financial Engineering
Michal Kolesár
Economics
Sanjeev Kulkarni
Electrical & Computer Engineering/Operations Research & Financial Engineering
S.Y. Kung
Electrical & Computer Engineering
Ching-Yao Lai
Geosciences
Naomi Leonard
Mechanical & Aerospace Engineering
Sarah Jane Leslie
Philosophy
John Londregan
Politics/Princeton School of Public & International Affairs
Anirudha Majumdar
Mechanical & Aerospace Engineering
Meredith Martin
English/Center for Digital Humanities
William Massey
Operations Research & Financial Engineering
Reed Maxwell
High Meadows Environmental Institute/Civil & Environmental Engineering
Prateek Mittal
Electrical & Computer Engineering
Ulrich Müller
Economics
John Mulvey
Operations Research & Financial Engineering
Arvind Narayanan
Computer Science
Kenneth Norman
Psychology/Princeton Neuroscience Institute
Jonathan Pillow
Psychology/Princeton Neuroscience Institute
H. Vincent Poor
Electrical & Computer Engineering
Yuri Pritykin
Genomics
Miklos Racz
Operations Research & Financial Engineering
Marc Ratkovic
Politics
Olga Russakovsky

Computer Science

H. Sebastian Seung
Computer Science/Princeton Neuroscience Institute
Amit Singer
Mathematics/Program in Applied & Computational Mathematics
Mona Singh
Computer Science/Genomics
Bartolomeo Stellato
Operations Research & Financial Engineering
Brandon Stewart
Sociology
John D. Storey
Genomics
Olga Troyanskaya
Computer Science/Genomics
Mengdi Wang
Electrical & Computer Engineering/Center for Statistics & Machine Learning
Samuel S. Wang
Princeton Neuroscience Institute
Michael Webb
Chemicanl & Biological Engineering