Visualization for Data Journalism
Explore effective data visualization methods using Python while mastering various chart formats and compelling storytelling approaches in journalism.
Explore effective data visualization methods using Python while mastering various chart formats and compelling storytelling approaches in journalism.
This course focuses on the visual presentation of data in journalism, teaching students to think critically about data visualization and create compelling graphics. Students will learn to make graphs similar to those in The New York Times, Vox, Pew, and FiveThirtyEight. The curriculum covers the history of data visualization in journalism, various chart types, visual perception theories, and narrative storytelling techniques. Practical skills include data wrangling, creating interactive charts and maps using Python libraries, and applying design principles. The course emphasizes hands-on practice and real-world application in newsroom settings.
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English
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What you'll learn
Understand the role of data visualization in modern journalism
Master various chart types and their appropriate uses
Apply visual perception theories to create effective graphics
Develop skills in data wrangling and preparation for visualization
Create interactive charts and maps using Python and Plotly
Learn narrative storytelling techniques for data-driven stories
Skills you'll gain
This course includes:
2 Hours PreRecorded video
7 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 6 modules in this course
This course provides a comprehensive introduction to data visualization for journalism. Students will explore the history and emerging trends of data visualization in newsrooms, learn various chart types and their applications, and understand the principles of visual perception and design. The curriculum covers data wrangling, creating interactive charts and maps using Python libraries like Plotly, and applying storytelling techniques to data. Participants will gain hands-on experience in creating compelling visualizations for news stories and learn to evaluate and critique existing data graphics.
Course Orientation
Module 1 · 1 Hours to complete
Module 1: Visualization in Newsrooms
Module 2 · 2 Hours to complete
Module 2: Data and Visual Perception
Module 3 · 4 Hours to complete
Module 3: Narrative Storytelling
Module 4 · 3 Hours to complete
Module 4: Cognitive Load and Color Perception
Module 5 · 5 Hours to complete
Course Conclusion
Module 6 · 5 Minutes to complete
Fee Structure
Payment options
Financial Aid
Instructor
Assistant Professor of Journalism and Computer Science at the University of Illinois Urbana-Champaign
Dr. Margaret Ng is an Assistant Professor at the University of Illinois Urbana-Champaign, where she teaches in both the Department of Journalism and the Department of Computer Science. Her research focuses on technology use discontinuance, information diffusion, and the role of social media in news contexts, employing a hybrid methodology that integrates big data analysis, machine learning, surveys, and experimental research. Dr. Ng earned her Ph.D. in Journalism from the University of Texas at Austin and has practical experience as an advanced analytics intern at Pew Research Center’s Data Labs, as well as a news artist and data reporter for notable organizations including National Geographic Magazine and The Center for Public Integrity. Her work aims to enhance understanding of user behavior in digital environments and contribute to more effective communication strategies in journalism.
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4.5 course rating
67 ratings
Frequently asked questions
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