5th Year Master's in Machine Learning-Machine Learning Department - Carnegie Mellon University

5th Year Master's in Machine Learning

Machine Learning and statistical methods are increasingly used in many application areas including natural language processing, speech, vision, robotics, and computational biology.  The 5th Year Master's in Machine Learning allows CMU undergraduates to complete a MS in Machine Learning in one additional year, by taking some of the required ML courses as an undergraduate. Students in this program take the same set of core courses as students receiving a PhD in Machine Learning, and also complete a Data Analysis Project.

Recommendations to students:

The program is open only to students that have taken 10-701 and received a grade of B+ or better, so students should aim to take this course by their junior year (or fall of their senior year at the latest).

It is important to be able to start on the Data Analysis Project (DAP) as soon as the 5th year begins. A good way to do this is to get started on related research during the senior year, as part of a senior project or one or more independent study electives. Another good way to get a head start would be to do research over the summer between the 4th and 5th years. A final way to get started early would be to begin doing some DAP research while taking the DAP preparation course in 5th-year Fall. Students who do not yet have research experience are particularly strongly encouraged to consider doing research during their senior year or the following summer.

Requirements for consideration:

  • Must be graduating with a bachelor's degree from Carnegie Mellon University.
  • Must have taken three of the courses during their undergraduate years. These courses may also be used toward the BS.
  • 10-701 (or 10-715) with a grade of B+ or better*
  • one elective (12 units, 600-level or higher)
  • one elective (9 or 12 units, 400-level or higher)†

The 600-level and 400-level electives could be one of the electives recommended for the undergraduate minor or the electives recommended for the master's. Other courses may be allowed on request.

*If your program rounds to the nearest letter grade so that B+ shows up as B, please let us know in your application so that we can verify your grade in 10-701. If you are taking 10-701 in fall of the senior year, let us know, and we will use your partial grade.
†You may use one 400- or 500-level elective taken as an undergraduate if its requirements are identical to a cross-listed graduate-level course, as indicated by the course syllabus or an email from the instructor. If the course is only 9 units, you should take at least 3 extra units as a master's student, such as with 3 extra units of research or by taking a mini-course.
  • Statement of Purpose (1 page)
  • Research Statement (1 page)
  • Endorsement from prospective Data Analysis Project (DAP) advisor, of the form "I have reviewed X's research statement and am happy to supervise this DAP research."

Program Requirements

60 units of core courses, 24 units of electives, 18 units of Data Analysis Project, and a 36-unit practicum for a total of 138 units.

All three Set Core Courses:

Plus two of the following Menu Core courses:

Plus two electives (24 units), taken as an undergraduate.

Plus DAP Project:

  • 10-821 DAP Preparation (6 units)
  • 10-611 MS DAP Research (12 units), taken the semester after DAP Preparation

Plus a Practicum (internship or research related to Machine Learning), generally conducted during the summer.

Students must be full time (have at least 36 units per semester).

A typical schedule for a student in the program might be:

  1. Courses taken in undergraduate program: 10-701 + 2 electives.
  2. Summer between 4th and 5th years: Practicum (internship or research related to Machine Learning). 
  3. Fall semester: 36-705 + a Menu Core course + 10-821 DAP Preparation (6 units) + 6 other units (possibly 10-611 MS DAP Research).
  4. Spring semester: 10-702 + a Menu Core course + 10-611 MS DAP Research (12 units).
Note: if other core courses (in addition to 10-701) have been taken as an undergraduate, then approved electives must be substituted for a total of 48 units to be counted as core courses.

How To Apply:

Submit the application, C.V., 1 page research statement, 1 page statement of purpose, and your unofficial CMU transcript by October 12th to:

Dorothy Holland-Minkley (dfh@cs.cmu.edu)
8001 GHC
Machine Learning Department
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213

Please have the prospective DAP advisor send email with their recommendation to Dorothy Holland-Minkley (dfh@cs.cmu.edu)