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

Traffic lights

Read about what's good

what should give you pause

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

Practical data visualization for news

According to learners, this course offers a solid foundation in data visualization for journalism. Many found the content highly relevant and practical, praising the focus on creating charts like those seen in major news outlets. The course covers key principles from figures like Edward Tufte and includes hands-on exercises using Python, particularly for creating interactive maps and standard chart types. While generally well-received, some students noted that the basic coding prerequisite is crucial, and those without a solid background in Python might find the technical aspects challenging despite the brief review module. The depth on certain topics was also mentioned as potentially needing more coverage for advanced learners.

Introduces fundamental visualization theories.

"Learning about Edward Tufte's principles and visual perception theories was a highlight; it helped me understand the 'why' behind good design."

"The modules on chart types, perception, and cognitive load provide an excellent theoretical backing for the practical exercises."

"The course does a good job explaining the core concepts and frameworks for effective data visualization."

Includes practical coding projects.

"The exercises creating line charts, bar charts, and scatter plots in Python were very helpful for practicing the concepts."

"Working on the interactive maps project in the final module was a great way to apply everything learned."

"The hands-on coding activities solidified my understanding and gave me practical tools to use."

Directly applicable to data journalism work.

"This course was incredibly useful for learning how to create news graphics and tell stories with data, just like the examples shown from NYT or Vox."

"I can immediately apply the techniques and principles learned here to my data journalism projects."

"Provides practical skills that are highly relevant for anyone working in or aspiring to data journalism."

Some topics could be explored more deeply.

"While the course provides a broad overview, I wish it had gone into more depth on advanced visualization techniques or libraries."

"The pace was good, but sometimes I felt like we moved on from a concept just as I was starting to grasp it deeply."

"Could use more examples or detailed explanations for complex data wrangling scenarios."

Requires strong existing Python skills.

"The course description mentions a basic coding review, but you really need more than basic Python knowledge to keep up with the exercises."

"Learners should have a solid grasp of Python before starting; the 'brief review' isn't enough if you're not comfortable with the language."

"I struggled with the Python coding parts as my background wasn't strong enough, despite the module 1 review."

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

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

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

Review core Python skills

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

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

Join a study group or online forum

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

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

Five other activities

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Learn about data visualization with Python

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

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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

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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

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

Solve data visualization puzzles

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

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

Create data visualizations on a topic of your interest

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

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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

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

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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