About this Course

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While telling stories with data has been part of the news practice since its earliest days, it is in the midst of a renaissance. Graphics desks which used to be deemed as “the art department,” a subfield outside the work of newsrooms, are becoming a core part of newsrooms’ operation. Those people (they often have various titles: data journalists, news artists, graphic reporters, developers, etc.) who design news graphics are expected to be full-fledged journalists and work closely with reporters and editors. The purpose of this class is to learn how to think about the visual presentation of data, how and why it works, and how to doit the right way. We will learn how to make graphs like The New York Times, Vox, Pew, and FiveThirtyEight. In the end, you can share–embed your beautiful charts in publications, blog posts, and websites.
This course assumes you understand basic coding skills, preferably Python. However, we also provide a brief review on Python in Module 1, in case you want to refresh yourself on the basics and perform simple data analysis.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Beginner Level

Basic Python

Approx. 17 hours to complete

English

Skills you will gain

Python Libraries
Data Analysis
Plotly
Data Reporting
Data Visualization (DataViz)

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Beginner Level

Basic Python

Approx. 17 hours to complete

English

Instructor

Instructor rating

4.33/5 (16 Ratings)

Margaret Ng

Assistant Professor

Department of Journalism

8,015 Learners

1 Course

Syllabus - What you will learn from this course

Week1

Week 1

1 hour to complete

Course Orientation

1 hour to complete

1 video (Total 3 min), 3 readings, 2 quizzes

3 hours to complete

Module 1: Visualization in Newsrooms

This module starts with a summary of the history and emerging trends of data visualization in journalism. You will then explore various types of charts and compare their pros and cons. By doing so, you will be able to recognize a wide variety of graphical forms and evaluate their capabilities/shortcomings as well as what situations each chart type is typically used in storytelling. We will also go through the classic reading by Edward Tufte, The Visual Display of Quantitative Information, and learn how to locate and articulate errors and deception in data visualization.

3 hours to complete

3 videos (Total 39 min), 2 readings, 1 quiz

Week2

Week 2

5 hours to complete

Module 2: Data and Visual Perception

In this module, we will first look at some examples of successful data visualizations in journalism. We will then drill down on numbers, learning the process of transforming data into information. Next, we will explore theories in visual perception and concepts in visualization and familiarize ourselves with the visual channel ranking—a useful guideline in designing news visualizations. You will evaluate pre-attentive attributes and why they are important in visualizations. You will also have hands-on practice to learn how data wrangling helps us make informed decisions.

5 hours to complete

3 videos (Total 35 min), 2 readings, 2 quizzes

Week3

Week 3

3 hours to complete

Module 3: Narrative Storytelling

In this module, we will learn about the frameworks and techniques that can be used to integrate visualizations into a narrative. You will examine the role messaging and interactions play in drawing readers into a story package that contains greater detail. For the hands-on exercise, you will start creating graphs in Python. You will apply design theories and concepts you previously learned to build line charts, bar charts, and scatter plots.

3 hours to complete

3 videos (Total 28 min), 2 readings, 1 quiz

Week4

Week 4

6 hours to complete

Module 4: Cognitive Load and Color Perception

6 hours to complete

3 videos (Total 37 min), 2 readings, 2 quizzes

Reviews

4.5

28 reviews

5 stars
74.24%
4 stars
15.15%
3 stars
4.54%
2 stars
3.03%
1 star
3.03%

TOP REVIEWS FROM VISUALIZATION FOR DATA JOURNALISM

by DCJul 12, 2020

Well organised and with a lot of commitment from the faculty. I would like to see deeper discussions on most of the topic in the future. Thank you

by SGMay 10, 2022

I truely enjoyed the contents and teaching in this online course. It's very helpful for my projects as an intern in journalism. Thanks so much, Dr. Ng. Amazing course.

by QYSep 22, 2020

Love her way of teaching, very clear and in a very good pace. I hope she can have more classes on Data journalism.

by SSFeb 9, 2021

The course can be bit more interesting with some suspense and current trending scenarios

View all reviews

Frequently Asked Questions

When will I have access to the lectures and assignments?
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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 purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
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.

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Visualization for Data Journalism