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)."

Source - Wikipedia: https://en.wikipedia.org/wiki/Data_science

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

• Jean-Nicholas Hould On Data Science: What is a Data Scientist? http://www.jeannicholashould.com/what-is-a-data-scientist.html
• DataViz: Six categories of Data Scientists http://www.datavizualization.com/blog/six-categories-of-data-scientists
• Data Science Central: No cost training to becoming a data scientist http://www.datasciencecentral.com/profiles/blogs/how-to-become-a-data-scientist-for-free-1
• Tech Republic: Why data science is just grade school math and writing http://www.techrepublic.com/article/why-data-science-is-just-grade-school-math-and-writing/
• Tech Republic: How to make yourself a DIY data scientist http://www.techrepublic.com/article/how-to-make-yourself-a-diy-data-scientist/
• Forbes: Data Storytelling: The Essential Data Science Skill Everyone Needs http://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/#fa0e678f0c8a
• CIO: IT career roadmap: How to become a data scientist http://www.cio.com/article/3057574/careers-staffing/it-career-roadmap-data-scientist.html
• Dataconomy: 5 Actionable Insights To Make You Stand Out In Data Science
  http://dataconomy.com/2016/04/5-actionable-insights-make-stand-data-science/
• ShapeScience: 10 pieces of advice to beginner data scientists
  https://shapescience.xyz/blog/10-pieces-of-advice-to-beginner-data-scientists/

Intermediate to Advanced

• Forbes: Improve Your Analytics Skills With These 9 Tips
  http://www.forbes.com/sites/metabrown/2016/12/31/improve-your-analytics-skills-with-these-9-tips/#6c2563781eb3
• SmartDataCollective: 7 Data Modeling Mistakes that Will Sink your Analysis
  http://www.smartdatacollective.com/eran-levy/431916/7-data-modeling-mistakes-will-sink-your-analysis
• Adobe Blog: Defining Machine Learning, Predictive Analytics, and Data Science — Without the Mumbo Jumbo https://blogs.adobe.com/digitalmarketing/analytics/defining-machine-learning-predictive-analytics-data-science-without-mumbo-jumbo/
• iamwire: Top 8 Big Data Tools for Enterprise Developers http://www.iamwire.com/2016/11/top-8-big-data-tools-for-enterprise-developers/132457
• TechCrunch: Facebook’s advice to students interested in artificial intelligence
  https://techcrunch.com/2016/12/01/facebooks-advice-to-students-interested-in-artificial-intelligence/
• MachineLearnings: The Non-Technical Guide to Machine Learning & Artificial Intelligence
  https://machinelearnings.co/a-humans-guide-to-machine-learning-e179f43b67a0#.4o4bv8axk
• PCMag: The Best Data Visualization Tools of 2016
  http://uk.pcmag.com/cloud-services/83744/guide/the-best-data-visualization-tools-of-2016

(Other) Interesting Reads

• People Profile - LA Times: IT career roadmap: How I Made It: Elena Grewal leads Airbnb’s data scientists http://www.latimes.com/business/technology/la-fi-himi-grewal-snap-story.html
• HBR: The Best Data Scientists Get Out and Talk to People https://hbr.org/2017/01/the-best-data-scientists-get-out-and-talk-to-people
• Forbes: The Rise Of AI Will Force Data Scientists To Evolve Or Get Left Behind http://www.forbes.com/sites/valleyvoices/2017/01/31/the-rise-of-ai-will-force-a-new-breed-of-data-scientist/#1e157fa432be
• Wired: 2016: The Year That Deep Learning Took Over the Internet https://www.wired.com/2016/12/2016-year-deep-learning-took-internet/
• TechInAsia: McKinsey finds it’s all talk and little action with data analytics in most companies https://www.techinasia.com/mckinsey-finds-data-analytics-sham

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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.

Check out his blog post 'How to Get a Data Science Job: A Ridiculously Specific Guide'

You'll be glad you did!

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