Visualization for Data Journalism from Coursera

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.

What's inside

Syllabus

Course Orientation

In this module, you will become familiar with the course, your classmates, and the learning environment.

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.

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.

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.

Module 4: Cognitive Load and Color Perception

In this final module, we will explore some related concepts of cognition and memory in visualization. You will examine the importance of using the “right” amount of color in the right place and apply Gestalt principles to de-clutter your data visualization. In the end, we will work on various exercises to create interactive maps with Python.

Course Conclusion

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides a clear path towards crafting graphs for online publications including those on websites, and blog posts

Mostly assumes basic Python knowledge of which it provides a brief overview

Consolidates all graphic design into the realm of journalistic inquiry

Provides data wrangling practice

Explores theories in visual perception

Survey's techniques used to integrate visualizations into narratives

Reviews summary

Well-received data journalism visualization course

learners say this well received course provides an entry-level overview on how to create data visualizations through python. Dr. Ng is highlighted as a talented instructor who clearly explains complex concepts. Students remark that the practical and engaging assignments helped them develop their programming skills and comprehension of the course material.

Students develop practical skills through assignments.

"The professor introduced the topic of data visualization in a very interesting and straightforward way."

"Her homework is scaffolding exercise that builds up your skills and confidence in using python to work on basic data visualization."

"This course is amazing and practical. Lectures were very interesting."

"Very interesting, clear descriptions and a lot of very useful information."

Highly regarded instructor.

"Dr. Ng laid has laid out a comprehensive course that covers the fundamentals all data scientists should know, with a unique emphasis on journalism. I am excited to continue learning more on this key topic!"

"Dr. Ng is clear and concise in her explanations and did a great job creating an entry-level overview course on data visualization which she obviously has a great wealth of knowledge."

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

"Very good professor! I would recommend taking her if you're not good at python."

Outdated coding assignments cause confusion.

"The content is good however it is very difficult to follow the Professor whose English is heavily accented."

"Please STEER CLEAR OF THIS COURSE. While the content of the videos is fascinating, they are completely unrelated to the coding assignments themselves."

"This course had a lot of great information and the instructor is extremely well-versed in the subject matter although a bit hard to understand when she's not on screen."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Visualization for Data Journalism with these activities:

Review basic statistical concepts

Show steps

By reviewing basic statistical concepts, you can strengthen your foundation and better understand the data visualization techniques covered in this course.

Show steps

Review your notes or textbooks on basic statistics.
Take practice quizzes or complete exercises.

Review core Python skills

Show steps

By refreshing your Python skills, you can better apply the advanced concepts covered in this course.

Show steps

Review the Python documentation on data structures and algorithms.
Complete a few practice problems using Python.

Join a study group or online forum

Show steps

By engaging with others, you can clarify concepts, share knowledge, and learn from different perspectives.

Show steps

Find a study group or online forum related to the course.
Participate in discussions and ask questions.

Five other activities

Expand to see all activities and additional details

Show all eight activities

Learn about data visualization with Python

Show steps

By exploring additional resources, you can deepen your understanding of Python and data visualization.

Show steps

Find tutorials on Python data visualization libraries like matplotlib and Seaborn.
Follow along with the tutorials and experiment with the code.

Read 'Visual Display of Quantitative Information' by Edward Tufte

Show steps

This book provides a comprehensive overview of data visualization principles and best practices, which can enhance your understanding of the concepts covered in this course.

View Beautiful Evidence on Amazon

Show steps

Read through the book and take notes.
Apply the principles to your own data visualization projects.

Solve data visualization puzzles

Show steps

By solving data visualization puzzles, you can improve your problem-solving skills and enhance your understanding of visual perception.

Show steps

Find online resources or books with data visualization puzzles.
Attempt to solve the puzzles.

Create data visualizations on a topic of your interest

Show steps

By creating your own visualizations, you can apply the concepts learned in the course and showcase your skills.

Show steps

Choose a dataset that interests you.
Clean and prepare the data.
Design and create your visualizations.
Share your visualizations online or with others.

Contribute to open-source data visualization projects

Show steps

By contributing to open-source projects, you can gain practical experience, learn from others, and make a meaningful contribution to the community.

Show steps

Find open-source data visualization projects on platforms like GitHub.
Identify areas where you can contribute.
Submit pull requests with your contributions.

Career center

Learners who complete Visualization for Data Journalism will develop knowledge and skills that may be useful to these careers:

Data Journalist

A Data Journalist gathers, analyzes, and visualizes data to tell compelling stories. This course will provide you with the skills you need to succeed in this role, including how to create clear and effective data visualizations, how to use data to support your stories, and how to communicate your findings to a wide audience.

See salaries and explore the career path for Data Journalist

News Artist

A News Artist designs and creates visual representations of news stories, such as charts, graphs, and maps. This course will help you develop the skills you need to succeed in this role, including how to create clear and effective data visualizations, how to use visual storytelling techniques to engage your audience, and how to use data to support your stories.

See salaries and explore the career path for News Artist

Graphic Reporter

A Graphic Reporter uses data visualization to tell stories and explain complex issues. This course will provide you with the skills you need to succeed in this role, including how to create clear and effective data visualizations, how to use visual storytelling techniques to engage your audience, and how to use data to support your stories.

See salaries and explore the career path for Graphic Reporter

Business Analyst

A Business Analyst uses data to improve business processes. This course may be helpful for those who wish to specialize in data visualization. You will learn how to use Python to create clear and effective data visualizations.

See salaries and explore the career path for Business Analyst

Statistician

A Statistician collects, analyzes, and interprets data. This course may be helpful for those who wish to specialize in data visualization. You will learn how to use Python to create clear and effective data visualizations.

See salaries and explore the career path for Statistician

Public Relations Specialist

A Public Relations Specialist manages the public image of a company or organization. This course may be helpful for those who wish to specialize in data visualization. You will learn how to use Python to create clear and effective data visualizations.

See salaries and explore the career path for Public Relations Specialist

Technical Writer

A Technical Writer creates technical documentation, such as user manuals and training materials. This course may be helpful for those who wish to specialize in data visualization. You will learn how to use Python to create clear and effective data visualizations.

See salaries and explore the career path for Technical Writer

Marketing Manager

A Marketing Manager plans and executes marketing campaigns. This course may be helpful for those who wish to specialize in data visualization. You will learn how to use Python to create clear and effective data visualizations.

See salaries and explore the career path for Marketing Manager

Science Writer

A Science Writer writes about science and technology for a general audience. This course may be helpful for those who wish to specialize in data visualization. You will learn how to use Python to create clear and effective data visualizations.

See salaries and explore the career path for Science Writer

User Experience Designer

A User Experience Designer designs and evaluates user interfaces. This course may be helpful for those who wish to specialize in data visualization. You will learn how to use Python to create clear and effective data visualizations.

See salaries and explore the career path for User Experience Designer

Information Architect

An Information Architect designs and organizes websites and other information systems. This course may be helpful for those who wish to specialize in data visualization. You will learn how to use Python to create clear and effective data visualizations.

See salaries and explore the career path for Information Architect

Developer

A Developer creates and maintains software applications. This course may be helpful for those who wish to specialize in data visualization. You will learn how to use Python to create clear and effective data visualizations.

See salaries and explore the career path for Developer

Market Researcher

A Market Researcher conducts research to understand consumer behavior. This course may be helpful for those who wish to specialize in data visualization. You will learn how to use Python to create clear and effective data visualizations.

See salaries and explore the career path for Market Researcher

Project Manager

A Project Manager plans and executes projects. This course may be helpful for those who wish to specialize in data visualization. You will learn how to use Python to create clear and effective data visualizations.

See salaries and explore the career path for Project Manager

Data Scientist

A Data Scientist uses data to solve business problems. This course may be helpful for those who wish to specialize in data visualization. You will learn how to use Python to create clear and effective data visualizations.

See salaries and explore the career path for Data Scientist