Knight Center Offers Massive Open Online Course on Data for Journalists

Mallary Tenore, Assistant Director, Knight Center for Journalism in America
Mallary Tenore, Assistant Director, Knight Center for Journalism in America

In order to expand online journalism education and for journalists to stay updated within the data revolution, the Knight Center is offering free Massive Open Online Course (MOOC) on how to find great stories in data.

The course “Intro to R for Journalist: How to find Great Stories in Data” is designed for journalists, editors, technology professionals, students and faculty, but is open to anyone with an interest in data analysis and visualization. It will run for five weeks July, 23 to August 26, 2018 and the instructor, Andrew Ba Tran, an investigative data reporter at Washington Post, will teach on how to use the programming language R to improve data analysis and reporting.

“You don’t have to be a data scientist to use R. In a few steps, will walk through how R can ask questions of data, whether it’s to explore a hunch or enhance an investigation,” Tran said. “We’re going to start with heaps of numbers, and end up with polished charts and maps — all while laying the groundwork to easily repeat these steps for your next project.”

Andrew Ba Tran will teach the basics of programming in R during week one and will dedicate week two to learning how to wrangle data to find cities where serial killers may have struck. During week three, students will create data visualizations using R. In week four, they will learn how to visualize geographical data using real Census and traffic stop data from the U.S. state of Connecticut to see where racial profiling might be happening.

And during week five, students will benefit from Tran’s emphasis on reproducible research, investigations that can be replicated using data and code provided by the researcher.  Journalists can create and customize notebooks from their data analysis and post them in HTML or PDF.

“Putting in the work to document and make your data analysis reproducible enhances transparency, builds trust among readers, promotes community, and makes it easier to share and update your work,” Tran emphasized.

After completing the course, students will be able to: import different types of data into R; wrangle, clean, join and analyze data; create exploratory and publishable visualizations; make static and interactive maps with geolocated data and Census data; join the reproducible research movement and publish their methodology.

The course is free, but students interested in obtaining a participation certificate must be active in discussion forums, successfully complete weekly quizzes and pay a US $30 administrative fee by credit card. No formal course credit is associated with the certificate.

For more information on how to register, please click here.