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Accredited Professional Development Data Science Course

Data Visualization with D3

Offered Live Online & In Person

This course provides a deep dive into D3.js, the JavaScript library frequently used to create data visualizations on the web. You will gain:

  • A working understanding of data visualization concepts, particularly related to the internet and mobile.
  • Deep knowledge of the forms and techniques of data visualization.
  • How to effectively display quantitative information.
  • Proficiency in using D3 to make static and interactive charts and documents
  • Proficiency in using JavaScript to process and manipulate data.

Course designed by Kevin Quealy, Graphics Editor at The New York Times.

Who the course is designed for:

Those seeking the power and control that D3 provides to tell stories and communicate information interactively in ways that simply are not possible outside of a web browser. They want proficiency in the use of D3 and expertise visualizing quantitative information. (Even if you're already an expert in JavaScript and D3, this course will help you select the right form, hone in on the best way to communicate your idea, and then build it.)


  • A working conceptual understanding of the field of data visualization, particularly as it relates to the internet and mobile devices.
  • Deep knowledge of the forms and techniques of data visualization and effective display of quantitative information, with a specific focus on bar charts, scatterplots, area charts, line charts, choropleth and bubble maps, small multiples, annotation principles – and the strengths and weaknesses of each.
  • Proficiency in using D3 to make static and interactive charts and documents and in using JavaScript to process and manipulate data.
Have questions? Get answers to frequently asked questions. FAQs

What you'll receive upon completion:

  • Certificate of completion
  • Up to 3.3 Continuing Education Units

Dates & Instructors

Check back soon for our next scheduled course.


This course is open to data visualization beginners but all should have experience writing HTML, CSS, and basic JavaScript. For HTML/CSS, you should know how to work with the DOM and be familiar with CSS selectors. For JavaScript, you should be familiar with variables, data types, arrays, loops, and conditional statements and you should have worked with functions and objects. 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:

Considering our immersive data science bootcamp?

Professional development alumni can apply the amount of tuition paid for one part-time course towards enrollment in an upcoming bootcamp upon admittance.

Course Structure & Syllabus

Week 1
Getting Started & Learning about New Problems

Configure computers, make first charts, understand why data joins are helpful, and get a sense of all the things we need to learn.

  • Introduction, configuring machines, intro to data visualization
  • Making our first chart: a scatter plot
  • Charting and intent
  • Bar charts
  • The fiddly bits: axes, formatting, etc.
Week 2
Enough to be Dangerous: Mastering Basic Forms

In order to be effective with data visualization, you need to master bar charts, line charts, scatter plots, and histograms. We'll make demos of each and learn when to use which.

  • Line + area charts
  • Histograms
  • Tables to line + area charts
Week 3
Data Sketching & Traversing Data Structures

Since your computer is drawing the charts instead of you, making 100 charts is as manageable as making one. We'll explore the power of exploratory sketching and the data manipulation you'll need to know in order to use it.

  • Making things move
  • Sketching in the browser and making applications that scale
Week 4

Mapping with D3 has exploded in recent years. Learn how to make bubble maps, choropleth maps, and topojson files from scratch.

Week 5
Making Dynamic Content

We'll use D3 to make dynamic charts and applications that let us answer questions and solve problems that wouldn’t be possible in a printed format.

  • Data visualization on mobile devices
  • D3 and Node
Week 6
Editing and Publishing an Idea

Focus on honing ideas and making publication-grade data visualizations. Work on small touches like custom annotations and styles, managing your data visualizations on mobile devices, incorporating feedback, and pitching work for publication. “Show and tell" of projects.

Live Online Interactive Learning

Learn from world-class data science practitioners.

Our Live Online instructors bring deep industry experience from a broad range of industries and companies including Viacom, Spotify, and Capital One Labs. You’ll have an Instructor and Assistant Instructor to support you throughout your learning process.

Interact with instructors and classmates in real-time.

This course is truly live, which means you can interact with the instructors and your fellow students in real-time. Stay engaged by asking questions and participating in polls and conversations, and join your course Slack channel for additional support, communication, and collaboration.

Learn online without sacrificing the value of live instruction.

The world is your classroom. Log in from wherever you are and gain access to live, interactive data science instruction that will push your career further in the right direction. In case you have to miss a class, you can access all recordings 24/7 to stay caught up and refer back.

Earn CEUs for accredited courses.

Not only will you walk away with new data science skills and knowledge, you’ll also earn up to 3.3 Continuing Education Units (CEUs). Our courses are accredited by ACCET, who requires we maintain high standards in areas such as quality of instruction and positive student feedback.

Register for an on-demand sample class

Our 1-hour on-demand sample class is a great way to preview what the Live Online experience is like for Data Visualization with D3.js professional development course.

Mollie Petit, instructor of the Data Visualization with D3.js course, will cover the following topics in the sample class:

  1. Beginner-friendly explanation of D3.js
  2. When to use (and when not to use) D3
  3. A look at some super cool D3 examples
  4. Followed by Q&A

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