A few months ago I became really interested in how to better utilize my economics skills and how to be a better job candidate.  Since I already had some background in computer programming, it seemed like a natural fit that I should pick up a programming language of some sort.  I poked, googled, hunted, and searched around for a bit until I decided on Python 3, mostly because it has a really strong community and is generally pretty friendly to newbies, along with being very powerful and versatile with a lot of data visualization tools, scientific packages, and web frameworks.  Strangely enough, one of the problems that I encountered was that there were almost too many resources and it has been tough to focus on just one and not hop around from tutorial to tutorial.  I’ve been uploading things semi-consistently to my Github account (BTW, thanks Github for having student accounts it’s a HUGE help to be able to put all of my tutorial projects/just starting out code into a private repo.  Since I’ve been working with Python for the last month or so, and after being more inspired to work on more ‘real world’ projects thanks to the hackathon I stumbled into the other night, I’m probably going to start branching out more and doing more useful projects to try and take off the training wheels as it were.

Below are some of the resources that I’ve used and some of my thoughts:

Overall, the last time I really programmed seriously was in high school with Visual Basic, so this was a generally different tack for me, but I’m really enjoying it and what I’m learning as well.

Books (available online/for free)

Learn Python The Hard Way, Zed Shaw: -http://learnpythonthehardway.org/book/ Synopsis: Zed Shaw uses Python 2.7, and the site/book gets somewhat of a bad rap for it.  The other thing that many other don’t like about it is the tone that Shaw takes when presenting problems oftentimes calling other programmers “arrogant” or “stupid”.  If you’re able to look past these excentricities though, the book isn’t bad at all and presents concepts fairly straightforward and explains issues very neatly and succinctly.  The other thing that I am very thankful for is how the book breaks things up into chapters and as such breaks things down/provides a logical flow to things.

How to Think Like a Computer Scientist, Downey, Elkner, Meyers -http://interactivepython.org/runestone/static/thinkcspy/toc.html# I’m only a couple of chapters into this book, but I’m loving it so far, not least because it is an interactive textbook that allows you to run code directly after reading about a concept.  Just like Shaw’s book, this one is broken up logically and simply with easy to follow examples and guidelines.

Automate the Boring Stuff, Al Sweigert -https://automatetheboringstuff.com/chapter0/ Another online book that comes highly recommended by the Reddit community just like How to Think Like a Computer Scientist.  I haven’t gotten too far into this book, despite the projects seeming VERY interesting, largely because I start to read through the chapters, but they seem never ending so I just move on to another resource that is able to show me/have me practice the concept that much quicker.  I have no doubt that I will work on these projects, but it’s just making the time to sit down and work through them.

There are other resources that I have used as well, that I will post here later/edit in.