In this e-Master Class you will gain insights on using public databases, internet databases, social media, information extraction to create powerful visualizations.
With more and more people relying on social medias and blogs to be informed, it is becoming increasingly difficult for the historic news outlets to attract an audience.
Data journalism is gathering, filtering and visualizing what is happening beyond what the eye can see has a growing value. By using the data to connects the dots, journalists can give meaning to little points of information that are often not relevant in a single instance, but hugely important when viewed from the right angle. And they can cover a wide range of topics such as the next financial crisis that is in the making, the economics behind the products we use, the misuse of funds or political blunders and then present it in a compelling visualization of the data that leaves little room for argument.
Working with data is like stepping into vast, unknown territory. At first look, raw data is puzzling to the eyes and to the mind. Data as such is unwieldy. It is quite hard to shape it correctly for visualization. It needs experienced journalists, who have the stamina to look at often confusing, often boring raw data and see the hidden stories there. And it is now possible for you to acquire these skills. By knowing how to develop simple codes, you can find the relevant information in databases which have millions of lines. You can also identify the names or the words in documents that would take centuries for a team of people to read through. Furthermore, you can increase your capacity to make sense of it all by developing graphics that give a totally new dimension to your story.
This Introduction to Computer Assisted Journalism is led by our partner, Columbia Journalism School and it will give you what you need to reach the next level in your profession.
The e-Master Class will cover the following topics:
This certified e-Master Class is for investigative journalists and data journalists who already have a basic knowledge of Excel or google sheets.
Columbia Journalism School has developed and organized this course to include six live lectures offered over three weeks.
Each session will take place from 16:00 to 17:45 CET (10:00 to 11:45 EST) on the following dates:
Module 1 (Pre-Recorded, 3 hours). Please complete this before Tuesday 8th June 2021.
Tuesday 8th June 2021
Module 2 (Live lecture, 90 minutes)
Thursday 10th June 2021
Module 3 (Live lecture, 90 minutes)
Tuesday 15th June 2021
Module 4 (Live lecture, 90 minutes)
Thursday 17th June 2021
Module 5 (Live lecture, 90 minutes)
Tuesday 22nd June 2021
Module 6 (Live lecture, 90 minutes)
Thursday 24th June 2021
Module 7 (Live lecture, 90 minutes)
Coding: Python programming (including scraping, regular expressions, panda, selenium, Beautiful Soup, SQL, DataScript
Data: Identifying and using large datasets to extract stories
Editorial: Getting access to a wider range of stories by connecting dots that are not readily available
Innovation: Computer assisted journalism opens new group in the field of journalism by allowing access to untapped sources of information like public databases, the web and social media
Storytelling: Using computer assisted journalism allows journalists to tell stories that would not otherwise be released
Strategy: At a time where blogs and Instagram acocunts are giving out 'news', to be able to produce data driven stories can be a way for historical news outlets to differentiate themselves.
SkillCoding Data Editorial Innovation Storytelling Strategy
08 - 24 Jun 2021
04 Jun 2021
Partners and Sponsors
The Columbia University Graduate School of Journalism is the premiere institution for the study and practice of journalism in the world. Led by their award-winning faculty of active reporters, editors, filmmakers and digital media specialists, their programs are intensive, rigorous, and demanding. Their professional development programs, fellowships and workshops offer opportunities for seasoned practitioners and media executives to advance their knowledge and expertise.