Wednesday 15 February 2017

Tech for The Techie: The Data Science Guide I never had

An Introduction to Data Science - Where do I begin?




 by Paul Ekwere
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It’s a very difficult thing to be interested in a very broad and ironically esoteric topic such as data science and know where to begin your research. The most difficult part of any great journey is taking that first bold step.

Unfortunately, not many of us know what that first bold step should be.

Welcome to Data Science 101.




There are quite a few varying opinions on what 'data science' is. Interestingly, the most apt definition I have read in recent days was on wikipedia.

Data Science (definition): " Data science, also known as data-driven science, is an interdisciplinary field about scientific methods, processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to Knowledge Discovery in Databases (KDD)."

As such, a data scientist, may be categorized as one who employs scientific methods, processes or tools to analyze structured or unstructured data to produce results that make the tasks of high level analyses, and drawing inferences and conclusions from the data simpler.

Data science is something I do everyday. It is something I have always done.
From my geeky love of weird sequences such as Fibonacci and hours spent as a pre-teen on my own creating my own unique logical sequences and custom cryptographic code, to my years as that-guy-in-class-that-doesn’t-use-a-calculator-to-do-his-math-but-rather-does-it-all-in-his-head, to my late teenage conquests of being that-guy-who-solved-the-rubik’s-cube-in-1-min-27-secs-flat-while-barely-even-looking-at-it-the-whole-time; to my latter years as an aerospace engineering student / honours graduate & now doing full-fledged data science work as a professional service, I have always been involved in one way, shape or form, in data science.

In my life as a data scientist, I have found that some things just come naturally to me. Other things, not so much. One thing though has stayed consistent. If I want an answer, I search for it. I find it!
If I’m puzzled by a problem, I ask, I read, I google, I annoy, I pester, until I solve it or find a solution!

Data science is exactly this!

  Be curious.
  Feed your curiousity.
  Find a problem.
  Fix it (or learn 1000 ways it can’t be fixed)
  Repeat above steps.

For a lot of people though, the first step is the hardest. So I thought I’d give you a little nudge in the right direction. Awaken that curiousity if you will.

I read a lot of posts on data science, analytics, machine learning and artificial intelligence. I also post every now and then on these topics on my twitter or my flipboard microblogs.
Among some of the things I have been reading, I thought it would be helpful to compile a list of some introductory data science topics & blogs I’ve recently read that may help. A basic guideline I wish I had when I first started my career.

They are, (in no particular order):

The Basics

Intermediate to Advanced


(Other) Interesting Reads

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UPDATE: Friday 24th February, 2017 @ 18:39 hours z
If you click through to none of those links above, you should definitely not leave this blog post without reading this.
Brandon Rohrer, Principal Data Scientist at Facebook puts it ever so simply.

You'll be glad you did!
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