Carnegie Mellon University

5th-Year Master's in Machine Learning

The 5th-Year Master's in Machine Learning allows CMU students to complete a MS in Machine Learning in one additional year by taking some of the required courses as an undergraduate. Interested students apply earlier in Senior year than the standard application deadline and receive the response earlier as well.

Requirements for Consideration

  • Must be graduating with a Bachelor's degree from Carnegie Mellon University.
  • Must take precisely 3 of the MS courses during their undergraduate years, passed with a B or better. (These courses may also count towards the Bachelor's degree.)
  • Must take 10-701 or 10-715 no later than the semester they apply; or must have taken both 10-315 and 15-281. (See "Recommendations to Prospective Applicants" below.)

Differences Between the Standard and Fifth-Year MS

Since 5th-Year MS students have taken 3 courses for the MS during their undergraduate years, the 5th-year MS can be completed in 2 semesters instead of the standard 3 semesters.

5th-year MS students must complete the program as full-time students (at least 36 units/semester) for two semesters plus a summer.

Typical Schedule

  1. Courses taken in undergraduate program: 10-701 or 10-715 Introduction to Machine Learning + 2 Core or Elective courses.
  2. Summer between 4th and 5th years: Practicum (internship or research related to Machine Learning). 
  3. Fall semester: 36-700 or 36-705 Statistics + 10-718 Data Analysis + a Core course.
  4. Spring semester: 10-716 Advanced Machine Learning: Theory and Methods + 2 Core or Elective courses.

Note: The program is designed for a Fall start, but a Spring start is possible. If a student will be graduating in December instead of May and so will be entering the Fifth-Year Master's in Spring instead of Fall, they are encouraged to take 36-700 in Senior Fall as one of the three courses taken as an undergraduate to count towards the master's degree, since it is good preparation for the remaining master's courses and is only offered in Fall. A standard course plan in that case would be 10-701 (or 10-315 + 15-281) no later than Junior Spring, 36-700 in Senior Fall, and the third course no later than Senior Fall.

Recommendations to Prospective Applicants

Students can take 10-701 or 10-715 as late as the semester they apply, but should aim to take it during Junior year. If you are taking it in the semester you apply, please authorize us to check your midterm grade.

Alternatively, instead of taking 10-701, a student may instead take both 10-315 Intro to ML for SCS Majors and 15-281 Artificial Intelligence. Together, these two courses can fulfill the 10-701 requirement. (Note that they will remain listed as 10-315 and 15-281 on the transcript, and the two of them together count as "one course" for the purpose of the Fifth-Year MS.)

Applicants should be aware that only 3 courses may double-count between the Bachelor's and Master's degree. Additionally, no courses can be triple-counted, such as being used for a minor, major, and the master's. Students will not be required to re-take courses, but may need to take additional electives if more than three relevant courses were taken before earning their Bachelor's degree.

Applicants should also be aware that we continually review our program requirements and update them as necessary to ensure an appropriate and up-to-date curriculum.  Please note that the program requirements applicable to you would be those in effect when your admission offer is made, which are not necessarily those in effect today. Our curriculum was tightened in Spring 2019 (from this older curriculum to this newer curriculum). In this particular case, applicants should be aware that courses taken after Spring 2019 must come from the newer curriculum, while courses from the older curriculum may be included in the application if they were taken in Spring 2019 or earlier.

The 5th-year MS application does not require GRE scores or digital portfolios, and only requires two letters of recommendation instead of three. However, if a student is planning to apply to other graduate programs if not admitted to the 5th-year MS, it may be advisable to prepare for those other applications as normal.

The tuition and fees for the 5th-year MS are the same as the standard MS. 5th-Year MS students are also considered graduate students, not undergraduates, and so should contact Housing Services if they're living on-campus or their financial aid provider if they have one to learn what effects this may have.

How to Apply

The next application deadline is March 9, 2022 for students applying to enter in Spring 2023. The next Fall application deadline will be in October.

Most students will apply in Senior Fall for entry Fifth-Year Fall, but there is a Spring admissions period for students graduating off-cycle. For example, students graduating a semester early can apply in Junior Spring for entry Fourth-Year Spring.

The application materials are:

  • Application form (PDF)
  • Statement of Purpose (1 page)
  • Resume or CV
  • CMU unofficial academic record
  • Mid-semester grades (required if Intro to ML is in progress; optional but recommended otherwise)
  • Two letters of recommendation, emailed directly to the Program Coordinator by the recommenders

For the Statement of Purpose, type a one page concise statement including: your objective in pursuing a graduate degree in Machine Learning; your background in particularly relevant fields; any relevant academic or research experience; and any additional information you wish to supply to the Admissions Committee.

The letters of recommendation may be written by anyone who knows the applicant well. If you have done research with a faculty member, a letter of recommendation from them would be ideal, but note that researh experience is not required. Recommendations should be emailed by the recommender themselves to Dorothy Holland-Minkley at dfh@cs.cmu.edu.

All materials submitted by the applicant should be in PDF format and the name of each file should begin with the string Surname_Givenname_ (e.g., "Carnegie_Andrew_Resume.pdf") to help with compiling. (Recommendation letters do not need to follow this format.)

All materials must be received by the application deadline for consideration that semester. The Program Coordinator will store any materials submitted early until the application deadline.

All applications should be submitted via email. Send them to the Program Coordinator Dorothy Holland-Minkley at dfh@cs.cmu.edu.

Additional Questions

For questions about the Machine Learning Master's Program that have not been answered on our webpages, please contact the Machine Learning Master's Programs Coordinator, Dorothy Holland-Minkley.

Dorothy Holland-Minkley holds office hours for prospective students during Spring and Fall. The Spring 2022 office hours are Thursdays from 2 - 3 PM on Zoom (Meeting ID: 957 7986 0085; Password: learning; CMU login required). The office hours aren't held when classes aren't in session (e.g., holidays and breaks).

You can also email her at any time at dfh@cs.cmu.edu.