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Visualization for Data Journalism

Approx. 18 hours to complete

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Course Summary

Learn how to effectively visualize data for journalism purposes in this course. Gain skills in creating compelling data visualizations that effectively communicate your message to your audience.

Key Learning Points

Learn how to create effective data visualizations for journalism purposes
Understand the importance of storytelling in data visualization
Gain skills in using data visualization tools such as Tableau and Google Fusion Tables

Learning Outcomes

Create effective data visualizations for journalism purposes
Understand the importance of storytelling in data visualization
Gain skills in using data visualization tools such as Tableau and Google Fusion Tables

Prerequisites or good to have knowledge before taking this course

Basic knowledge of data analysis
Familiarity with spreadsheets

Course Difficulty Level

Intermediate

Course Format

Online
Self-paced
Video lectures
Assignments

Similar Courses

Data Visualization and Communication with Tableau
Data Visualization with Python

Related Education Paths

Notable People in This Field

Edward Tufte
Nathan Yau

Related Books

Description

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.

Outline

Course Orientation
Introduction
Syllabus
About the Discussion Forums
Updating Your Profile
Orientation Quiz
Demographics Survey

Module 1: Visualization in Newsrooms
1.1 Data Visualization in Journalism: History and Development
1.2 Types of Charts and Graphs: Choosing the Right Chart for the Right Task
1.3 What Makes a Good Data Visualization?
Module 1 Overview
Module 1 Reading
Module 1 Quiz

Module 2: Data and Visual Perception
2.1 Journalism First
2.2 Drilling Down on Numbers
2.3 Data Visualization & Visual Perception
Module 2 Overview
Module 2 Reading
Module 2 Quiz

Module 3: Narrative Storytelling
3.1 Narrative Storytelling 1
3.2 Narrative Storytelling 2
3.3 CRAP: The Principles of Design
Module 3 Overview
Module 3 Reading
Module 3 Quiz

Module 4: Cognitive Load and Color Perception
4.1 How Color Communicates Meaning
4.2 Gestalt Principles
4.3 The Role of Memory in Vision
Module 4 Overview
Module 4 Reading
Module 4 Quiz

Course Conclusion
End of Course Survey

Summary of User Reviews

Read reviews for Visualization for Data Journalism course on Coursera. Users rated the course highly and praised its practical approach to data visualization. Learn about the pros and cons of the course before enrolling.

Key Aspect Users Liked About This Course

Users appreciated the practical approach of the course, which focuses on real-world examples and case studies to teach effective data visualization techniques.

Pros from User Reviews

The course provides clear and concise explanations of key concepts in data visualization.
The assignments and exercises are challenging but rewarding, and help to reinforce the lessons learned.
The course is well-structured and easy to follow, even for beginners with no prior experience in data visualization.
The instructors are knowledgeable and responsive, providing helpful feedback and guidance throughout the course.

Cons from User Reviews

Some users found the course to be too basic, and wished that it covered more advanced topics.
The course can be time-consuming, particularly for those who are new to data visualization.
Some users found the assignments and exercises to be too difficult, and struggled to complete them on time.
The course may not be suitable for those who are looking for a more theoretical or academic approach to data visualization.
The course does not cover all of the tools and software used in data visualization, and users may need to seek out additional resources to learn about these.

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