When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Fundamentals of Data Visualization

3 days left! Save on skills that make you shine with 40% off 3 months of Coursera Plus. Save now

Fundamentals of Data Visualization

This course is part of Vital Skills for Data Science Specialization

Instructor: Danielle Szafir

8,602 already enrolled

Included with

Learn more

3 modules

Gain insight into a topic and learn the fundamentals.

43 reviews

Intermediate level

Recommended experience

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

Build toward a degree

Learn more

3 modules

Gain insight into a topic and learn the fundamentals.

43 reviews

Intermediate level

Recommended experience

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

Build toward a degree

Learn more

What you'll learn

Develop a toolkit for exploring and communicating complex data using visualization
Produce basic data visualizations using a chosen dataset
Compare methods for visualizing data and understand how these methods may guide users towards different conclusions
Evaluate how effectively a visualization conveys target data

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is part of the Vital Skills for Data Science Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

Data is everywhere. Charts, graphs, and other types of information visualizations help people to make sense of this data. This course explores the design, development, and evaluation of such information visualizations. By combining aspects of design, computer graphics, HCI, and data science, you will gain hands-on experience with creating visualizations, using exploratory tools, and architecting data narratives. Topics include user-centered design, web-based visualization, data cognition and perception, and design evaluation.

This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

Module details

In this module, you will learn the foundations of visualization design. You will walk through the key components of a visualization, how we effectively represent data using channels like color, size, and position, and some ground rules for honest and effective visualization. You will also gain preliminary exposure to Altair, a Python library for rapidly generating interactive visualizations. Each week will also include either two readings or one reading and one notebook activity.

What's included

13 videos17 readings2 assignments2 discussion prompts2 ungraded labs

13 videosTotal 157 minutes

Course Overview3 minutes
Why Visualization?14 minutes
A Grammar of Graphics11 minutes
Introduction to Altair7 minutes
Hands on with Altair - Part 113 minutes
Hands on with Altair - Part 212 minutes
Mapping Basics11 minutes
Mapping Tips12 minutes
Color18 minutes
Rules of Thumb17 minutes
Introduction to Interaction13 minutes
Interactions Part 114 minutes
Interactions Part 212 minutes

17 readingsTotal 161 minutes

Course Updates and Accessibility Support1 minute
Earn Academic Credit for your Work! 10 minutes
Course Support10 minutes
Assessment Expectations10 minutes
AI Citation and Acknowledgement10 minutes
Assessment Expectations10 minutes
A Tour Through the Visualization Zoo10 minutes
Data Humanism: The Revolutionary Future of Data Visualization10 minutes
Vega-Lite: A Grammar of Interactive Graphics10 minutes
Workshop Overview of Altair Basics10 minutes
Exploratory Data Visualization with Altair10 minutes
The Structure of the Information Visualization Design Space10 minutes
Extra Resources: Data Types, Graphical Marks, and Visual Encoding Channels10 minutes
The Good, the Bad, and the Biased10 minutes
Extra Resources: WTF Visualizations10 minutes
Extra Resources: Ethical Dimensions of Visualization Research10 minutes
Toward a Deeper Understanding of the Role of Interaction in Information Visualization10 minutes

2 assignmentsTotal 35 minutes

AI Policy Quiz5 minutes
Week 1 Quiz30 minutes

2 discussion promptsTotal 20 minutes

Introduce Yourself10 minutes
Visualization Project Part 1: Finding your Data10 minutes

2 ungraded labsTotal 120 minutes

Introduction to Altair60 minutes
Implementing Interaction in Altair 60 minutes

In this module, you will learn how to choose the right visualization for a given scenario. You will learn how to reason about the different kinds of questions people ask with visualization and, how to align your design with that task. The module will cover basics of task analysis, methods for task elicitation, and foundational knowledge of visual perception for design. Each week will also include two external readings or one reading and one notebook activity.

What's included

9 videos7 readings1 assignment1 discussion prompt

9 videosTotal 110 minutes

Visualization Tasks13 minutes
Task Elicitation16 minutes
Basic Design Methods12 minutes
Design Studies17 minutes
Perception Overview6 minutes
Preattention14 minutes
Attention & Search14 minutes
Uncertainty11 minutes
Ethical Questions8 minutes

7 readingsTotal 70 minutes

A Design Space of Visualization Tasks10 minutes
Design Study Methodology: Reflections from the Trenches and the Stacks10 minutes
Overview: The Design, Adoption, and Analysis of a Visual Document Mining Tool for Investigative Journalists10 minutes
Criteria for Rigor in Visualization Design Study10 minutes
On the Prospects for a Science of Visualization10 minutes
Attention and Visual Memory in Visualization and Computer Graphics10 minutes
Why Authors Don't Visualize Uncertainty10 minutes

1 assignmentTotal 30 minutes

Week 2 Quiz30 minutes

1 discussion promptTotal 10 minutes

Visualization Project Part 2: Sketching your Data10 minutes

In this module, you will learn how to assess the effectiveness of your visualization. You will learn both qualitative and quantitative approaches for evaluating visualizations as well as how to isolate key elements for assessment and iteration. The module will cover basics of insight-based evaluation, interview studies, and experimental design and analysis. Each week will also include two external readings or one reading and one notebook activity.

What's included

7 videos7 readings1 assignment1 discussion prompt

7 videosTotal 80 minutes

Module Overview2 minutes
Evaluation Overview8 minutes
Defining Insight12 minutes
Qualitative Evaluation16 minutes
Experimental Evaluation Part 114 minutes
Experimental Evaluation Part 217 minutes
Evaluation Trade-Offs11 minutes

7 readingsTotal 70 minutes

Empirical Studies in Information Visualization: Seven Scenarios10 minutes
Toward Measuring Visualization Insight10 minutes
Criteria for Rigor in Visualization Design Study10 minutes
Experimental Research in HCI10 minutes
A Design Space of Vision Science Methods for Visualization Research10 minutes
Empirical Studies in Information Visualization: Seven Scenarios10 minutes
Evaluating Information Visualizations10 minutes

1 assignmentTotal 30 minutes

Week 3 Quiz30 minutes

1 discussion promptTotal 10 minutes

Visualization Project Part 3: A Plan for Evaluation10 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Build toward a degree

This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹

Instructor

Instructor ratings

(13 ratings)

Danielle Szafir

University of Colorado Boulder

1 Course8,602 learners

Offered by

University of Colorado Boulder

Learner reviews

5 stars
79.06%
4 stars
13.95%
3 stars
4.65%
2 stars
0%
1 star
2.32%

Showing 3 of 43

Reviewed on Dec 16, 2023

Very Lively interaction from the mentor. Simplified explanations

Reviewed on Jan 23, 2026

Not your basic data visualization course - very in depth and interesting with concepts that are fresh and new. Professor is very thorough and understandable.

View more reviews