So it’s really Spring here in Minnesnowta. We didn’t have a winter, per se but if we had, it would be over by now. 

The daffodils are blooming, Dinkytown has traded hoodies and duckboots for sundresses and sandals, and another quarter of the year is gone in a blink.

For me, Spring is when I take inventory and re-calibrate everything.  This year’s calibration may be more of a tectonic shift than anything.  Big changes are coming soon — long overdue changes.

I’ll have plenty to keep me busy, I’m sure but just in case I get bored, I’m looking into the possibility of work paying for me to retake both Stats 1 and Discrete Math. A refresher in Stats would be quite timely since it’s been about 10 years now, and our Prof in Discrete last summer was just hopeless (and helpless). So there’s that. I’ll take both over the summer, if I can. I could just tough it out and learn them again from a book, but I do much better with some structure around it to keep me focused.  Otherwise I get very “look, a chicken!” ADD about stuff.

In the meantime I’m still learning a ton, but have encountered what has to be a #nerdworldproblem of #firstworldproblem proportions:

Now that there’s an actual field {data science} that encompasses my various domains {math, *nix, epistemology, etc}, there is a plethora of learning to be done in many areas. I am, as they say, drinking from the firehose.

So I need to get some structure into this. I mean, I could literally spend every waking moment of my life doing nothing but free OpenCourseware classes from MIT. Or the Coursera Machine Learning/Crypto/AI/CS classes from Stanford. Or Python the Hard Way. Or Khan Academy. Or Or Or.

Choices simply must be made. And I’m not historically good at narrowing down options. But let’s see where we are so far. 

Things I’ve decided NOT to do:

• Learn Ruby — Perl (and a bit of Python) are enough for scripting
• Learn a low-level language — This may change. Julia has promise but C is just painful shorthand for Assembler and ASM just sucks
• Become a statistician — Data Science:Statistics::Predicting:Explaining and I’m most interested in the former
• Give up on the idea of a PhD — I can do this
• Limit my options to the local metropolitan area — It’s a big world and I’m not old yet

Thing I’ve decided to KEEP doing:

• Practicing sed/awk/grep along with Perl
• Learning new tools like Google Refine
• Learning more math

Things I’ve decided to START doing:

• Sell off my 35mm camera gear to raise money for a truly badass laptop
• Send my medium format film off for developing and scanning since I don’t seem to be doing it myself
• Getting a Twin Cities Datageek meetup together at least once a month
• Going to the R User Group meetup
• Train up to get onto a Kaggle team
• Some personal life-oriented stuff that noone else cares about

That’s a lot of change. And bigger changes are on the way.

Or, as Neddard Stark said: Winter Is Coming.