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
Related Topics for further study
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
IntermediateCourse 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.
Margaret Ng
4.4 Raiting
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