I am wrapping up my undergraduate degree in CS, and I've done a bit of specialization in AI/machine learning through these courses: IR, CompLing, Data Mining, Robotics. I also have some research experience applying machine learning to computer vision/object recognition for robotics. At this point I would say I have an "OK" general understanding of various ML concepts: classifiers, clustering, association rules, ANNs, etc. However, I don't really have a deep understanding of the math behind these things, as my undergrad courses mostly glossed over those details.
I have been accepted into a MS CS program at a highly ranked university (top-5 in AI). It will take me an additional 3 semesters of school to get the Masters vs. leaving with just a BS. I am trying to decide if I need to continue with the MS degree. I really like learning, and would LIKE to do the degree, but the opportunity cost is weighing on the decision.
My career goal is to become more than a general software engineer. I like ML and related (vision, robotics, NLP, etc), and it seems like it's both interesting and practical to industry. Ideally I would have a job where I keep up with the state-of-the-art and apply it to the needs of the organization. Another great job would be doing applied (or basic) research. I'm more interested in solving technically hard problems that say going to Scrum meetings, talking about unit tests and deployments, etc. I'm not saying those aren't necessary, but if that's ALL I do at work I could not stand it. I should also mention that I have substantial "general" software engineering experience and I like coding. I chose to go back to school to do something more interesting. The question now is whether to continue to the Masters or stop with a Bachelors. PhD is not realistic for me in my situation.
I would love to hear from people who work with ML, AI, etc in industry, including level of education required. Thanks!
tl;dr: How much education is required to get an ML job in industry?
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