An Introduction to Data Science - Where do I begin?
by Paul Ekwere
___________________________
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
______________________________________
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!
______________________________________
Leave a comment or share this post if you found it useful.
Follow @paul_ekwereii Tweet to @paul_ekwereii
