Course designed by Kevin Quealy, Graphics Editor, The New York Times.
Data Visualization with D3.js Overview
D3 can be challenging to use, and much of the difficulty comes with learning syntax and understanding data joins (the most fundamental aspect of D3). On top of that, there are the headaches associated with the minutiae of charts: scales, axes, labels, annotations and the like.
But that extra effort becomes worth it when you realize that with D3, you're in charge of every pixel. That power and control enables you to tell stories and communicate information interactively in ways that simply are not possible outside of a web browser.
Who is this course for?
Anyone who wants to be proficient in the use of D3 and seeks expertise visualizing quantitative information. This course will not train you to become a data scientist. (For that, we offer a licensed, accredited bootcamp).
Considering the data science immersive bootcamp?
Part-Time Alumni can apply the amount of tuition paid for one part-time professional development course towards enrollment in an upcoming bootcamp upon admittance.
For Git and GitHub, you should be familiar with forking, cloning, pull requests, and branches.
Finally, you should have a general idea of working with and manipulating structured data.
If you don't yet have this fluency, we strongly recommend completing the following free tutorials in advance of the course start:
Git & Github: Complete Documentation
HTML & CSS: Web track - Codecademy
Intro to D3
Command-line (first two sections): Codecademy
Upon completion of the Data Visualization with D3.js course, students have: