Toggle Mobile Menu

Machine Learning Certificate

Master in Finance

Machine Learning Certificate

In partnership with the Center for Statistics and Machine Learning (CSML) at Princeton, Princeton BCF began offering Master in Finance students the opportunity to earn a Certificate in Machine Learning in spring 2019.

All students enrolled in the Master in Finance program for four semesters are eligible to earn the certificate by meeting several requirements. Students who complete the program in one year are not eligible.


Certificate Requirements

While Princeton BCF and CSML have identified several pre-approved paths students can take to earn the certificate, the program’s academic advisors may approve other ways to satisfy the certificate’s requirements.

Master’s students enrolled in the CSML certificate MUST have a minimum GPA of 3.50 at the start of the spring semester in their second year in order to be eligible to earn the certificate at graduation.

While requirements one and two listed below are mandatory for all students,, students may seek approval to swap the courses listed in requirement one for other courses. Students wishing to pursue other options should contact Susan Johansen at csmlgrad@princeton.edu.

Finally, note that with the approval of the Director of Graduate Studies, some of the courses listed below could be counted as elective credits towards the Master in Finance degree.

The certificate requirements are comprised of three key components:


Pre-approved Pathways 

  1. Completion of graduate seminar SML 510. Students must enroll and complete the requirements of the CSML graduate seminar, SML 510. Note that it does not provide a credit toward the Master in Finance degree and is offered both semesters.
  2. Research Component, which consists of the completion of a paper written as part of FIN 561 in the spring semester of the student’s second year. It is highly recommended that students take at least a core or an elective Machine Learning course before enrolling in FIN561. FIN 561 is preceded by meetings between students and a BCF faculty member.  These meetings will define students’ research interests and discuss the structure of a research dissertation. In January, each student enrolled in FIN 561 will have settled on an advisor, a paper concept—and corresponding data analysis project—necessary to satisfy the requirement. Completion of the research project and preparation of the paper will be completed throughout the semester under the supervision of a BCF faculty.
  3. Course Requirements: Students must take for credit (and receive an average GPA of B+ (3.3) or better) three courses from CSML’s approved list of courses.  The three course categories are:
  • One Core Machine Learning Course. Master in Finance students can choose between ELE 535, COS 402, COS 524, COS 485, and COS 511. NOTE: COS courses are not always offered (e.g. COS 402). COS 524, COS 485, and COS 511 are typically offered in the spring.
  • One Core Statistics and Probability Course: Master in Finance students can choose between ORF 524, ECO 513, ECO 519 and ELE 530. These courses are typically offered in the fall.
  • An Appropriate Elective Course: Master in Finance students interested in machine learning and its applications are encouraged to consider elective courses such as ORF 522 in the fall; and ECO 515, FIN 580, ORF 523 and ORF 525 in the spring.