
Ask HN: Minimum viable transition to AI? - howhireable3141
Briefly, I am a mid-30s full-stack (or generalist) developer of no particular pedigree (college dropout, mostly self taught, small time consulting, and working for small technology startups).<p>I was &#x27;good&#x27; at math as a kid but neglected it as I was older and, as a result, have always been intimidated by ml&#x2F;ai.  Until recently, I had it in my head I missed the boat on having the math foundation necessary to do ai.<p>On a whim (while on sabbatical), I took Geoffrey Hinton&#x27;s Neural Network course.  This required significant tangential studying to get my linear algebra and calculus up to snuff.  All in all, I spent about a month where most of my time was either spent on Hinton&#x27;s course or the math foundations necessary to understand it.<p>Feeling very excited, I was looking for what to study next, assuming I could probably get myself hire-able within a year or so--in the meantime, I would consult in my &quot;old&quot; work, and build a couple portfolio pieces (my first is just about done already).<p>Searching the internet and asking around in AI chatrooms, I came across the fast.ai courses.  A few weeks after that (this week), I have a tenuous grasp of how to use pytorch, especially with the fast.ai library, and I am able to get shockingly decent results on my own applications of the techniques.<p>Now I wonder if there is enough demand for deep learning practitioners that I might be able to continue my learning as a junior in a lab somewhere more or less immediately.<p>My end goal is to build robots that will facilitate mass automation of human labor.  And, to do it in a way in which the technology&#x2F;IP behind the automation will be public&#x2F;free of patents and restrictions.<p>Salary&#x2F;location not particularly important.<p>Given all of the above, what does the minimum viable CV look like to start getting income in this space?  Is there room for non-seniors to grow into capable researchers?<p>Thanks for any insight.
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p1esk
Your CV must include links to ML project(s) you've completed.

In fact, various datascience/ML fellowships exist for this very reason - to
help people like you to complete a project and get hired.

You can see who was hired where after completing a project [1], and example
projects [2]. Insight Fellowship is just one of many [3]. Just don't confuse
these programs with AI research fellowships at FAANG labs (those are pretty
hard to get into, and typically require publications in top conferences to be
considered).

[1]
[https://www.insightdatascience.com/fellows](https://www.insightdatascience.com/fellows)
[2]
[http://xyz.insightdatascience.com/blog/](http://xyz.insightdatascience.com/blog/)
[3]
[https://www.google.com/search?q=ai+fellowship](https://www.google.com/search?q=ai+fellowship)

Good luck!

