I work as a software engineer at a U.S. university that is arguably tops in the world in AI/ML. I took advantage this semester of our free tuition benefit and enrolled in a graduate-level intro to machine learning class. Given my full-time work and family responsibilities, the course proved to be a lot of time and work - but in the end I learned tons and did well enough that I'm considering pursuing a professional master's degree in ML here.<p>My goal with getting the degree is to remain relevant in this industry as a technical contributor (I'm in my early 40s), open up new opportunities, and very simply to make more money. Pursuing the degree, though, is a significant time and effort commitment: it will take me about four calendar years (taking one class at a time) to complete. The opportunity cost of pursuing it is spending more time with my family, having less stress, being able to work on side projects from time to time, etc.<p>I'm curious to see what folks in the HN community think. On one hand it seems like an absolute no brainer that I should take advantage of this. On the other hand... I dunno.
Getting a job at a large tech company like Google, Facebook, Amazon, or a startup, will likely teach you about applied ML much quicker than a school will (with likely much higher pay too). I guess it depends on your end goal though. Working at a university is typically pretty relaxed, so it probably is a no brainer, especially if you get some type of pension.
A key question is: Did you enjoy taking the class?<p>The love of money is a dangerous mistress.<p>When you have a family at home, spending time studying can often feel like you are cheating your kids out of your being a good dad.<p>You can keep yourself relevant without a masters. Can you get a Grad certificate? Or can you learn a lot on your own? In your current job? Better yet can you get your university to pay you a salary while you go to school full time?
I am a software engineer that works full time (and have a family:), and have just handed in my masters thesis. What made it easier for me was picking a problem I was already very familiar with (and passionate about) to do my thesis on. After that it was just putting in consistent hours in the evening after everyone went to sleep.
Maybe think of it incrementally in the sense that you can start out with the goal of pursuing a masters, with each completed course adding to the completion of that goal as well as adding to your current knowledge and skillset, with the understanding that at any point in time it might make sense to stop.
You have a job, first-hand experience from within a top environment in ml and a family? In your shoes, I would gently ask my direct supervisor to test the waters and eventually take the master’s path in case a new / better paid job is lined up for me in advance through the internal route.