This may be obvious, but I wanted to ask anyways. Currently I’m considering my grad school options, mainly so I can work as an ML Engineer afterwards. A lot of the schools I’m looking at have professional/non thesis options. I was wondering, would a non thesis masters hurt my chances of working in the ML field if I didn’t really want to get a phd afterwards?
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If you’re not doing a thesis, be sure you have original projects or work experience to talk about during your interviews.
Especially for ML, hands-on experience is so important even just for learning. And is unfortunately under-emphasized in many ML courses.
I think it depends on whether you want to go into a more researchy or more practical MLE role. I did the capstone project track, and don’t regret it as it let me pursue a larger variety of projects, and I could also do an independent study that ended up being kinda Thesis Lite™. If you do a full thesis then the majority of your time in grad school will be spent on just one project, and a lot more academic research than practical engineering. It will definitely set you up better for doing more cutting edge stuff in the industry, which could potentially be more fun/interesting, but if you try to take your career in that direction then you’ll be competing against a lot of people with PhDs.
I don’t think it makes a difference unless you can publish it somewhere recognizable / gain high academic impact. In this case, thesis programs might grant you more time (taking less course) and mentorship to achieve that goal.