Note: Just to be up front, I'm very well-read on data science and getting into the field, so I'm not looking for generic "try this" suggestions, but am really after recommendations specific to me and my situation. Not to be an ass, but I wanted to point that out up front.
TL;DR
- Previous experience in IT, programming, data analysis
- Current MS CS student looking to get into data science or machine learning research
- Grad certificate in data mining
- Some research in ML on the way, looking to leverage this
- What other experiences/credentials/etc. would offer a good ROI trying to break into data science or ML research?
So first a little background:
- CS undergrad degree (BS), graduated in '07 from Canadian university - program provided solid programming, theory, math foundation, etc., all of the "regular" CS undergrad stuff
- Pre-BS work experience in IT (system admin, DB admin)
- Post-BS work experience in IT (system admin, programming) and as a data analyst at a governmental health oversight agency ("big data")
I am a current CS master's student at a US state institution, anticipating a spring 2015 finish. I am completing all of my studies at a distance (online), but have made a few visits to the institution and will eventually make a few more. There are numerous reasons I pursued this route which made sense for me at the time, and which are irrelevant to this discussion. Ideally I would have relocated to matriculate at a top institution in person but, alas, that was not in the cards.
All aspects of the program thus far have uniformly exceeded my expectations. Besides theoretical and practical gains all-around, some points of note:
- Programming abilities & confidence are now next level, with some additional programming and algorithm courses still to come
- Numerous additional languages added to my skill set
- Of (unfortunate) note, my institution does not offer (pure) machine learning classes as opposed to what is covered in data mining course
- I specifically tailored a very technical and rigorous program and passed over what I would categorize as "fluffier" courses (no "management" courses) which I believe has paid off
- Upcoming thesis on ML or DM (will nail down specifics with advisor [AI professor] next week)
- Upcoming independent research course project in programming languages realm - looking to combine parallel, cloud, parsing with DB design and come up with a usable piece of software; admittedly nothing too groundbreaking, but hopefully a comprehensive “look what I can do”
- I have a few papers on arXiv and have been asked to submit some things for publication (no guarantees, obviously), and hold out hope a thesis produces something publishable
- FWIW I'm a straight A student, in undergrad, grad and certificate program
I am also finishing up the UCSD data mining certificate, completing my final course next month. I started it nearly 2 years ago and have intentionally spread it out over the course of my grad degree. The program has covered machine learning algorithms, data mining technologies, and provided a solid theoretical & practical foundation.
Additionally, I have also taken a bunch of Coursera courses, generally the ones you would expect me to list at this point (ML, Johns Hopkins DS courses, UW data science, programming languages, compilers, etc.). I have also undertaken some self projects, with some others lined up, and am looking to put together a solid portfolio of my work over the next semester (data science-style projects), and have some of my better lower & higher level programming projects (less DS-related) on github.
My question, then, is this: What additional credential/project/experience/etc. would best help break into the worlds of ML research or data science? I'm sure a home run of a thesis wouldn't hurt, nor would a favorable outcome with my research project artefact, a few independent projects that gain some social media media traction or a couple of published papers. Pursuing a PhD in ML would be my top choice, but that isn't going to happen at this point either, realistically, and so I consider some of these other options:
- Machine Learning Summer School 2015 (somewhere) - contacts, good speakers, others sharing interest, cheap and quick
- Zipfian Academy or similar boot camp - generally good outcomes, but I'm Canadian and can't participate in hiring day (although as a Canadian getting US work permission is easier than other foreign nationals [no guarantees]); more expensive, but again, likely good outcome
- Pursue a kick-ass internship - could lead to a job, who knows, more uncertainty than boot camp (though cheaper)
- Something else???
A little more info:
- Canadian, looking to work (and live) in Canada, US or Europe (EU passport [likely] on the way, and I passably speak a couple of EU languages)
- Non-traditional student (mid-30s), family, kids, looking to start as high up on the food chain as possible & prove self afterward
- Cliche, but very passionate about data, and even getting to understand machine learning I am still fascinated by it and view it as wizardry
I know I'm not going to compete on paper with most PhDs, but if I can do something more to stand out among other non-PhDs and genuinely improve my knowledge base I would certainly consider it. If you feel that I am kidding myself here with my goals based on my situation, please feel free to express that opinion as well.
I also know there is no replacement for on the job skills and learning, but as a bit of an intellectual I don't mind extending "schooling" a bit longer and coming up with the best positioning for myself when I hit the job market. My goal is not cushy mid-management somewhere; I genuinely want to innovate and ambitiously contribute to something bigger than myself.
If you have gotten to the end of this and have something to contribute, I would genuinely be very interested in reading it. Please forgive my verbosity.
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