Learn to Code by Making Visualizations
Making interactive visualizations is an exciting way to also learn computer programming. That's what Obama did. You can learn both programming and interactive visualization skills in two ways: (a) though web devevelopment and (b) through data analysis.
|Description||Key learning outcomes|
|Learning through web development|
|Learning through data analysis environments|
As detailed above, each learning pathway has its pros and cons, but both involve learning some computer programming. If you haven't programmed before, then great! Making visualizations is a fun way to start learning. If you have programmed, then learning interactive visualization skills will be even easier.
When learning visualization skills, I found many great individual blog posts and tutorials, but struggled in finding a curriculum that pieced together all of these learning resources. Hence, subsequent posts will take will take a more "meta" approach that will outline various learning pathways and direct you to relevant resources.
My next post will focus on the web development learning pathway. In the meantime, here are some (free!) resources about learning more general web development skills:
- Codecademy's courses don't assume prior programming experience. However, as someone with prior programming experience, I still found them useful especially for learning new syntax. I was only mildly irrirated by the slow pace of the courses. But the somewhat slow pace suits a broad audience (e.g., they have over 24 million learners!).
CodeSchool's course on Chrome DevTools: I highly highly highly recommend that you learn how to use a web development environment like Chrome DevTools or Firebug before getting deep into making visualizations. I didn't myself, which was a rookie mistake that I now regret. Like Codecademy's courses, CodeSchool's course on DevTools is interactive and I also highly recommend it.
Chapter 3 from Scott Murray's book: Provides a brief, highly accessible overview of core web development technologies. It's a fairly dense summary, so I recommend using it as a "reference guide" for when you get deeper into more specific topics.
Think I've missed a route for learning interactive data visualization? Tell me so in the comments!