I'm a guy with a bachelor's degree in computer science who's been working for 2 years as a full-time Software Engineer. I want to apply for a master's degree in either Applied Statistics or Data Science so that I can do research in a specific area of interest, but I have zero previous research experience, zero connections with professors and very limited background knowledge other than the barebones courses I did in my undergrad degree.

I read basically everywhere (reddit, Facebook, etc) that you need to cold-email professors and comment on their research to be able to get in so the solution I thought of is to learn the pre-requisites on my own and work on a project to create a portfolio like you would if you were applying for a job. I have spent half a year on learning pre-requisites like Linear Algebra and I have a much deeper understanding now but there is still much more left. It could take me an entire year to even be able to comment on the latest research.

What do I do? Should I continue learning? Am I wasting my time? Should I just apply to a program in the hopes that they will teach me the pre-requisites as part of the program?

I've been feeling frustrated and directionless lately because I have no examples to guide me in this situation and the speed at which other people get into master's programs makes it feel like I'm being left behind.

  • 7
    What country are you planning to apply for a masters?
    – Buffy
    Commented Jun 18 at 22:25
  • 34
    "It could take me an entire year to even be able to comment on the latest research." Certainly what is expected of applicants can differ from country to country, but I am quite confident that whatever country you are in does not in fact expect people applying to a Master's programme to comment on anyone's latest research. This does not ring true even for a PhD programme, much less a Master's. Commented Jun 18 at 22:53
  • @Buffy While I don't have strict requirements for which country to apply to, my first choice is Canada. Commented Jun 18 at 23:09
  • 28
    "I read basically everywhere (reddit, Facebook, etc) that you need to cold-email professors and comment on their research to be able to get in" - for getting into a master's degree?? I've never heard that and as far as I know admission procedures (statistician, have been at various European universities) this kind of thing is never required, and you won't make yourself friends in this way as everyone receives too many emails anyway. Commented Jun 19 at 9:01
  • 8
    I’d think MSc program websites would be a better source of information than Facebook and Reddit. Although specialised Reddit subs, eg for students of a particular university, can be informative. Commented Jun 19 at 10:19

5 Answers 5


You absolutely do not need to cold email professors and and be able to discuss their research to get into a program.

Master's programs in the US (and I have to assume in most places with a similar university structure) generally are not expecting significant research background or particular prerequisites past what one would take in a related undergraduate degree. As long as you are willing to pay tuition, you can find a good Master's program. Even research-based Master's are not really going to be expecting much more, other than a willingness to do research. You'll probably find/be assigned a research mentor once you're already accepted into the program.

Honestly, rather than trying to learn on your own, it's probably a better use of your time to just start looking at programs, putting together an application, and sending it. Any program you go to will teach you what you need to know. That's the whole point of graduate school. If you already knew everything in the field (or even enough to hold an informed discussion about current research) you wouldn't need to go in the first place.

  • 9
    Great answer, just one addition: If a prerequisite is explicitly listed in the program description an OP realizes he's lacking knowledge in this area (e.g. it's a course he did not take) then - and only then - would self-studying prerequisites be the right thing to do.
    – Sabine
    Commented Jun 20 at 11:30
  • 2
    This is also true in the UK. I was accepted to a computer science (taught) masters programme at a russell group university based on pretty much the exact same qualifications as the question asker. There may of course be requirements that the bachelor's degree is a certain grade. I did pre-study some maths prerequisites to help me keep up with specific modules but my acceptance to the programme was unrelated to that.
    – deee
    Commented Jun 20 at 13:47

Because you said your country of choice is Canada and everyone else has talked only about the US or Europe, here's a Canada-specific answer – which is, like for many things, kind of "in between" US and Europe. (For context, I'm a professor in computer science working on machine learning, so statistics-adjacent, at a top Canadian research university; I did my education in the US and a postdoc in Europe.)

Canadian master's programs in applied stats / data science come in two flavours, which are very different from one another.

One flavour is a "professional master's." This is more common for things called, say, "master of data science"; these programs are course- and/or project-based, and aimed at getting you a job as a data scientist. They're more often 1 year, sometimes 2. These programs charge substantial tuition (my university's program is C$35,000 for Candian citizens + permanent residents, C$55,000 for others, with some amount of aid/loans available but it's going to be Expensive). They are very industry-focused and do not really focus on preparing you for research, but do prepare you for data scientist-type jobs. (Whether these programs are useful to you might also depend on the particular program, what you did in your undergrad, and what you've been doing in your SWE job since; there's a fair amount of variety in how much they teach you CS things versus specifically data things.) Most US master's programs fall more into this category, though there's a bit of a range.

I am not very familiar with the process for getting into professional master's programs, but you certainly do not need to contact professors for it; you need to convince whatever admissions committee that you're motivated, qualified, and likely to succeed. Talking about your self-study in an application essay, if applicable, may be a very good thing, but you also may have some trouble getting in if there are many prerequisites you don't have official "proof of." It might help to take a course for credit somewhere as a non-degree student; this will be much easier if you've already self-taught the subject! But this is going to vary a lot depending on which particular master's program you're looking at.

The other flavour of master's is a "research master's." Here you take courses, receive a stipend (probably based at least partially on TAing, and the amount varies dramatically across Canadian universities), and as a large component of the program do novel research with a faculty supervisor. These are typically two years, although at least here people often take three. This degree roughly corresponds to the first few years of a US PhD; if things go well on both ends, it's common for people to continue on with a PhD with the same supervisor, but it's also common for people to switch to do PhDs with someone else / at a different university, or to go get a job instead. (There is typically much more research involved than a European master's; although not a strict requirement, the general expectation in my department is that master's students complete at least one project corresponding to a publishable paper in a top venue before they graduate. This is somewhat different in statistics, where publication is slower, but not super dramatically.)

For people applying to research master's in computer science departments (and I think stats is not too different), it is absolutely the expectation that you will be able to talk about research when applying. It's not that you need to have smart things to say about every professor you're interested in's research or that you're expected to know everything already (certainly not), but the general expectation at least for the students I admit is that you should have both a strong coursework background in related areas, and ideally have done a little bit of research of your own already to have a sense of what it's like and that you like doing it. Not having done any research before is not necessarily disqualifying, but you need to stand out in some way from the many applicants who have done that. Different people put differing amounts of weight on this, though, and many don't care at all, just look for people who look smart + motivated. So, if you don't have an immediate path towards doing research (and most people won't)...look smart + motivated.

(Having a specific problem you want to work on is a mixed bag; it can be a good sign that you know what you're talking about, but also the potential advisor might be worried that that's the only thing you're interested in and maybe that doesn't align with what they care about.)

For getting into these programs, pre-existing contact with professors is complicated. If I know who you are and have a positive impression of you, there's a much stronger chance that I'll pay attention to your application. But if you send me a cold email that says "I found your work on [clearly copy-pasted paper title from my website] so inspiring!," I'm not going to reply, if I even open it – there's a flood of those emails at admission time, which are generally clearly extremely low-effort. So...one strategy is to put effort into contacting a few professors, make it immediately obvious from your email that you've made that effort, and even then accept that many of those emails will not be read. Given that that's a lot of effort for low probability of payoff, you can also just not email anyone, and just make your application the strongest you can make it.

In terms of prerequisites: I'm not exactly your target audience, but honestly I would be very leery to admit someone who hadn't taken and done reasonably well in a formal linear algebra course. If it's just that you're refreshing some tools you haven't used in a while, great! But if you've never taken linear algebra / multivariate calculus / probability / ..., getting into a data-oriented Canadian research master's may be difficult, and so might succeeding in that program if you do get in. If you're just missing a bit, you can probably catch up, but if you're missing a lot, it'll make everything much harder.

So, learning these topics is a great strategy, but "I self-studied X topic" on your CV is hard for me to really trust. If something else is drawing me to your application, I could give you a "math test" and have you convince me that you do know these topics – but I'm not going to put that effort in unless there's something else convincing me that doing this is worth my time and effort. So, again, getting course credit for any major missing topics – maybe after you've self-studied – would help with this path too.

  • This answer is very relevant. Fortunately, I have done formal courses in Linear Algebra(got a B+) and Probability and Statistics(got an A) during my CS program. But after I did my Final Year Project and graduated, I realized I never really got the core concepts that you'd need for research. Just enough to pass the grade. I know now I should focus more on applications but I definitely feel pretty rusty since I never needed those concepts after graduation. Commented Jun 23 at 13:00
  • Oh, in that case self-study is great! These are important tools and being more fluent with them will only make it easier to succeed in a data-oriented grad program. It may or may not have any real impact on your chances of getting in, but will definitely help if you do go.
    – Danica
    Commented Jun 24 at 23:16

If your goal is to conduct academic research in the US, then strong prior coursework (that are not self-studied) and prior research experience are much valued when applying to PhD programs. I personally think it is more efficient to network with researchers and even perhaps do some research engineering for them. While program prerequisites are useful, they are much less useful than good recommendation letters or hands-on research experience. Perhaps self-studying is a useful as a data point to support that you are indeed passionate about research.

I read basically everywhere (reddit, Facebook, etc) that you need to cold-email professors and comment on their research to be able to get in so the solution I thought of is to learn the pre-requisites on my own [...]

For masters program decent academics in undergrad (and perhaps some good LoR) is more than enough. For research-based masters or PhD prior research experience or contributing to research in any capacity is imo more useful than cold-emailing.


From the standpoint of graduate applications, then as other people have said, I don't believe that self-study is necessary or all that helpful.

That said: if you want to study applied statistics or data science, then mastering linear algebra was definitely not a waste of time!

Should I just apply to a program in the hopes that they will teach me the pre-requisites as part of the program?

Having some gaps in your prerequisites is very common. Your professors might teach you -- but being able to learn on your own is an important skill in graduate school, and I expect that your professors might offer you some help and guidance but expect you to mostly self-study any missing prerequisites. So, possibly, you did already what you would otherwise need to do anyway.

As the leading answer suggests, I'd encourage you to apply to programs directly, without worrying too much about learning prerequisite material. If you do have time to learn prerequisites on the side, then this might pay off once you begin a graduate program.

Best of luck!


We don't know who answered on reddit or facebook, but I'd like to throw in that from a German (maybe European) perspective, there might be some misconception involved.

In Germany, when someone talks about "graduate students", many people think of PhD students. The reason is probably that in earlier times, students graduated with a Diplom or Magister that is equivalent to a masters degree today, there was no equivalent of a bachelors degree.

For someone aiming for a PhD, cold-mailing professors and commenting on their research can be a good idea, though there are many other ways to get a PhD position or a spot in a PhD program - my PhD advisor preferred to "hand pick" PhD students among those master students who attended his lectures, others did publish their job openings just like any other employer would do.

For a masters, this is absolutely not necessary. A regular application, typically through the university website, is all it takes. Self-studying prerequisites should not be necessary unless they are explicitly listed in the program description.

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