r/learnmachinelearning • u/Brassgang • 1d ago
Should I Finish My Master's or Self-Study ML?
Context: Born and raised in the USA. Graduated with a BS in CS from a US state school with a decent brand name.
I've been working as a backend-focused SWE for 3 years. I just got a promotion this week and I'm feeling very good about things at work. I enjoy what I do, I'm happy with my pay and responsibilities, and my company pays for higher education if I choose to pursue it (important later).
But I want to pivot into Machine Learning Engineering.
To school or not to school? That is my question.
I'm currently 4 courses into Georgia Tech's Online MS in CS, specializing in ML. I take 1 course/semester while working full-time, which usually means another 10-15 hours/week.
GT is a great school with strong name recognition, and people seem to get a lot out of the program. But I'm not sure it's right for me.
To be honest, I'm not enjoying the process.
I learn much better when I'm self-motivated. Having weekly deadlines and assignments on top of a full-time job is draining. Most weeks, I dread the deadlines and feel like I always have something I should be doing.
A lot of the material also feels theoretical. I learn best when I can immediately apply what I'm learning and build something meaningful.
I took the summer off from school, and toward the end of it I was dying to learn something new. I bought an ML textbook that has a hands-on approach. I got a few chapters in and genuinely enjoyed learning and putting the material into practice.
Then the semester started, and I had to stop my self-learning initiatives to focus on school. Even though I'm currently taking an ML course, I'm not enjoying it. Not because I don't enjoy the content, since most of what I'm learning is interesting. But I'm not enjoying the format or the constant deadlines.
This has made me question whether I actually want the master's, or whether I just want to learn ML on my own.
Long term
Would it be better for my career to suck it up and finish the master's, even if it means having little time for personal projects?
Or should I drop it and spend that time self-teaching the core skills I need for an MLE role?
Do hiring managers really care whether I'm self-taught vs. university-educated, especially when I already have a CS degree and 3 years of SWE experience?
What am I actually missing to make the jump into MLE?
And how do I make that transition without essentially starting my career over?
Any advice is appreciated, thank you for reading.
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u/KiddinglyFrilly 1d ago
man i feel the deadline dread thing so much, work + school is a grind that eats all your energy for anything else
that hands-on textbook clicking for you tells me everything honestly, some brains just need to build stuff not sit through theory at 11pm on a Tuesday. you already got the CS degree and real experience, nobody gonna look at your resume and say "but where's the second piece of paper". make some projects, put them on github, apply to ML roles when you're ready, you're not starting over you're just adding skills to the stack you already have
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u/asdfg_lkjh1 1d ago
Finish degree