
Ask HN: Is an AI CS degree worth getting for an SWE with 10+ years experience? - throwaway170820
(Note: I asked this yesterday and it got deleted for some reason, so I am trying again).<p>I have been an SWE for about 10 years, in my early 30s now. I make good money in this profession (in Europe). I have a bachelor&#x27;s degree in Computer Science.<p>I am wondering if now is a good time to get a master&#x27;s degree in CS (focusing on AI). I have taken lots of AI courses on Coursera and can build neural nets to accomplish non-trivial problems, but my AI foundation is not great.<p>The reason I am conflicted about a degree is because I am not sure if my work post-degree would actually change or if it would truly open more doors for me. I even work at an AI-focused company, but the AI &quot;thinking&quot; work is always outsourced to researchers&#x2F;Ph.Ds in the field.<p>My job as a software engineer is to be an executor&#x2F;implementer of the models they come up with. If I had a solid grasp of AI, but remained a programmer, would my job prospects change? To be clear, I do not want to become a researcher -- I prefer the software side of things.<p>But I don&#x27;t know what an SWE with a solid AI foundation even works on. How is the work different from that of an SWE <i>without</i> the AI foundation?
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syllogism
Just keep working. Masters programs suck anyway --- the only things that
really make a difference are a) time, b) conversations with peers, c)
conversations with an advisor. When you're 22 a PhD is a reasonable deal to
spend 4 years to get this. When you're 32 it's a significantly crappier
bargain.

If you get good at designing the models, your results will speak for
themselves, and it won't matter whether you have a certificate saying you can
design models. Likewise if you're actually bad at something you're supposedly
certified to do, I think that's actually worse than not having the
qualification at all!

The simplest thing to do is just pick a problem with a decent dataset and work
on it. Either build the model from scratch, or if you prefer to use a library,
make sure you're compiling the library from source. You want to make sure you
can change arbitrary things --- don't just use an API.

If you're interested in NLP, I can suggest a number of things you might work
on for spaCy :). For instance, I'd like to have a sequence-to-sequence
lemmatisation model. This will take some experimentation, but the basic idea
should definitely work.

If you need any more convincing not to do a masters...Really think about what
that will involve. You'll go to lectures. You'll get _homework_. You can do
better than that.

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throwaway170820
Thanks for your response. I tend to what you are saying by my actions (not
getting a degree), but I wanted to make sure I wasn't just convincing myself
it would be a drag to go back to school.

I agree with most everything you said, but somewhat confused by "When you're
22 a PhD is a reasonable deal [...] When you're 32 it's a significantly
crappier bargain," because I'm just rearranging years of my life, right? I
mean, a 22 year old who had the possibly to enter the workforce also had an
opportunity cost, albeit lower than mine now. Is that the intent?

~~~
syllogism
Education is always more efficient when you're younger. Imagine the limit: if
you have five years until retirement, spending them on training won't maximise
your earnings!

There are roughly 45 years in a career. If you do a PhD at 32 you only have
about 30 years to exploit the degree.

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eshvk
There are roles called Machine Learning Engineers/Research engineers. The work
does require enough background in ML; as in it is non trivial to implement an
algorithm, consider approximations while scaling without knowing how the math
works.

Although, you might be able to get away with not knowing recent ML work by
having a solid education in linear algebra, probability and statistics.

