Disclaimer: The descriptions on this page are the personal opinions of Dorothy, not CMU or the City of Pittsburgh.

What is Pittsburgh like?

The answer depends on where you're from. The city itself is about 300,000 people (the 67th-largest city in the U.S.), while the metropolitan area is over 2 million (the 28th-largest metropolitan area in the U.S.).

If you're from a midsized city, Pittsburgh has everything you could want: arts (symphony, ballet, multiple museums including some that are free to students), sports (football, baseball, hockey, soccer), nature (rivers and parks with miles of biking and walking trails), restaurants, shopping, nightlife, and more.

If you're from NYC, you'll likely be surprised that you can walk from CMU to residential neighborhoods where 10 p.m. is considered a late closing time for the local shops. If you're from LA, you might be surprised that walking or biking to campus is perfectly reasonable and many students, staff and faculty members do so all year. If you're from Florida, you're going to be forming strong opinions on snow boots in January.

For photos of the city and tourist-type stuff, check out www.visitpittsburgh.com.

What is CMU like?

Unlike many top universities, CMU has a compact campus. A "long" walk between buildings is five to 10 minutes and usually doesn't involve crossing any streets. A student in the Machine Learning Department can attend most classes, seminars and research group meetings while never leaving the Gates-Hillman Center or the connected Newell-Simon Hall. Anyone who wants to go off campus for lunch can get to the restaurants on Craig Street with a seven-minute walk from Gates-Hillman.

While Pittsburgh has excellent sports teams, collegiate sports aren't a major focus of CMU's social life, nor does CMU have a party-school culture. Instead, large social events at CMU tend to be either geeky or artistic. One of the largest events each semester is Capture the Flag With Stuff, where hundreds of students play capture the flag with over a dozen varieties of magic items. The biggest celebration each year is Spring Carnival, where students enjoy carnival rides, eat typical fair foods, and check out booths (tiny buildings filled with art and games) built by fraternities and clubs that are designed from scratch each year around a set theme.

The Machine Learning Department itself is close-knit. We occupy the eighth floor of the Gates-Hillman Center, and students and faculty often have quick chats while getting bring-your-own-mug coffee, tea, or hot chocolate in the kitchenette. The M.S. in Machine Learning program shares a lounge/study space with the M.S. in Computer Science program directly across the street in the Tepper building, just a few minute's walk away. The monthly Machine Learning Tea is always well-attended by graduate students, faculty and staff relaxing and chatting over snacks, and students regularly enjoy getting together for on-campus board game nights and off-campus rock climbing.

For a view of campus itself, check out the CMU Visit page, the campus map, a virtual tour, or scroll through the CMU flickr.

What is housing like?

CMU does not have graduate student housing. Most graduate students rent apartments in either Oakland (the neighborhood CMU is in) or the adjacent neighborhoods of Shadyside and Squirrel Hill.

CMU's Graduate Student Association hosts a housing resources webpage, including a Graduate Student Housing Handbook with detailed information about housing costs, neighborhoods and how to find an apartment.

If you want something super close to campus and don't mind living near undergrads, consider Oakland. If you want something more upscale, try Shadyside. If you crave quiet, Squirrel Hill is for you.

Can I fit research into the program?

About half of our students are engaged in research in any given semester. Along with research that's done purely for fun, three out of nine courses can be replaced by research, and the summer practicum can similarly be completed via research. This means that our M.S. students can complete the program  with the same schedule as our Ph.D. students, completing two courses plus research each semester and doing research over the summer. Check out our full curriculum.

How would I find a research adviser?

It's the student's responsibility to find a research adviser, but we do have a standard method. The easiest way to match with an adviser is to wait until you're here, which is how our Ph.D. students do it. While some programs assign advisers to applicants when they're admitted, we instead want to give new students the opportunity to meet all our faculty in person before deciding on an adviser. The main way we facilitate this is through the departmental orientation at the beginning of the semester, when most of our faculty give twenty-minute research talks. We encourage the faculty to make it explicit whenever possible whether they are seeking Ph.D. or M.S. advisees — or both. It isn't uncommon for an adviser to have a strict cap on the number of Ph.D. students they're able to advise (since that is a many-year commitment) while they can be more flexible on how many M.S. students they're able to advise.

After listening to the talks, you can then reach out to any faculty you'd be interested in working with to set up a brief meeting to discuss your skills and interests. If you and the faculty member agree that you're a good match, you can begin working together at any time.

Students who already know they want to do research can start looking for an advisor over the summer. ML research under our Core Faculty is pre-approved for Independent Study credit, while a project under our Affiliated Faculty would require approval to confirm it's sufficiently related to ML. Students can look at faculty's websites over the summer to see what kind of research they do and begin to make a tentative list. Generally, that list will both gain and lose entries based on what you hear during orientation, because faculty's presentations can surprise you.

Students who are feeling particularly ambitious can start reaching out to Ph.D. or M.S. students in those research groups over the summer to get a feel for what day-to-day life is like in the group or what kind of background they'd need to succeed in that field of research. A simple email saying "Hi, I'm an incoming MSML student, would you be up for a 15-minute chat about your research?" can go a long way. Your fellow graduate students can't officially add other members to their research groups, but they can be an invaluable resource when searching for one you'd be happy in.

When could I begin research?

The timing for an M.S. student to begin research depends both on the individual student and their adviser. A student with a strong and relevant research background may be able to jump into a project in their first semester. A student without that background or who's entering a new research area may instead spend the first semester sitting in on their new adviser's research group meetings and doing background readings instead of participating in a project right away. Waiting also lets the student complete three courses in their first semester, which is helpful for students who haven't had an opportunity to study machine learning before.

Are research assistantships available?

Research assistantships for M.S. students are fairly rare. Approximately 10% of our master's students earn some form of RAship in any given semester. The extent of this RAship depends on the grants that their adviser has available in any given semester. For example, some grants require that RAships only be given to Ph.D. students and so M.S. students aren't eligible for payment. Another grant might be able to provide hourly pay to anyone regardless of class level. A different grant might offer tuition remission in exchange for a semester of work. However, most M.S. students simply complete research for credit.

Do note that since you won't be able to form a research relationship until after you arrive, you'll unfortunately have to make your decision about whether to join our program without knowing if research funding would be available.

Are teaching assistantships available?

Teaching assistantships are much more common than research assistantships. After you've completed a course, you're welcome to apply to be a TA for it. TAs earn hourly pay and many master's students TA. Learn more about becoming a TA.

How do I find an internship?

CMU's Career and Professional Development Center (CPDC) starts supporting students with online modules for students to work through in the summer before the program begins, to get them ready for career fairs. The career fairs generally start in the first couple weeks of classes, and continue throughout the Fall and Spring based on when different industries do their hiring. The CPDC holds workshops on various topics throughout Fall and Spring, as well as doing one-on-one advising for things like resume review, job offer negotiation, or how to transition to a new field.

In terms of job postings, those are collected by both the CMU-wide CPDC (which posts them on Handshake) and also the School of Computer Science's career's team, which forwards them to students via email as well as hosting events.

In the opposite direction, the CPDC collects resumes from interested students and proactively sends a resume book to employers as well.

For networking, there's the CMU-wide CMUniverse that connects students and alumni, and there's also a private MLD LinkedIn group that's only open to current and former MLD students, faculty, and staff, meaning that you can use it to connect with someone who's currently working at your desired company and they'll know exactly how good the MSML program is. This is especially useful for employers that give a boost to applications if a current employee gives it a "thumbs up."

Can I talk to someone about the program?

The Machine Learning Master's Programs Manager, Dorothy Holland-Minkley, is happy to talk with prospective students at any time. You can email them, and telephone and video chats can be arranged as well.

Several current machine learning master's students and MSML alumni have volunteered to speak with prospective students as well. Email Dorothy to request to be put in touch with them. If there are any aspects you're specifically interested in (such as international student issues, research experiences or undergraduate major), you're welcome to mention that and you'll be matched with relevant students as much as possible.