Learn more of what AI can do for you

[NEW!] Hands-on Machine Learning for Journalists

A free online course designed by JournalismAI in collaboration with Texty and the support of the Google News Initiative.

The course works as a complement to our Introduction to Machine Learning (see below) and teaches journalists how to use ML for their reporting. By taking the course, you will learn how to train a Machine Learning model to identify and classify images in vast datasets.

The course is hosted on the Training Centre of the Google News Initiative, and was launched on 7 December 2020.

Take the course online and don't forget to let us know if the course was useful so that we can improve future resources. Sign up for the JournalismAI newsletter to stay informed about new training materials and all our activities.


Introduction to Machine Learning for Journalists

A free online course designed by JournalismAI in collaboration with VRT News and the support of the Google News Initiative.

Through examples of journalistic applications, this course will help you understand what machine learning is, how it works, and how you can use it in your reporting.

The course is hosted on the Google News Initiative Training Centre and includes 6 modules that can be explored independently – although we recommend taking them in the suggested order to get a complete overview:

  • Machine learning, journalism and you
  • Is machine learning the same thing as AI?
  • Different approaches to machine learning
  • How you can use machine learning
  • How does a machine learn?
  • Bias in machine learning


Learn more of what AI can do for you

With the global survey that led to the publication of the JournalismAI report, newsrooms across the world highlighted the urgent need for education and training on AI-related topics. A better understanding of AI was seen as vital to change newsroom culture and facilitate the adoption of these new technologies. In the words of one of the survey respondents:

"Literacy is crucial. The more the newsroom at large embraces the technology and generates the ideas and expertise for AI projects, the better the outcome, in our experience."

As part of our mission to foster AI literacy and understanding of its potential and implications for journalism, we want to make sure that everyone has access to the best online training resources. We are doing that by curating existing materials, as well as creating online courses ourselves. Here are our recommendations:

7 things to consider before adopting AI in your news organisation

In 7 steps, this free course develop by the JournalismAI team will help you understand what AI is and is not, how these technologies are already used in journalism and what value they can bring to your newsroom. You will learn what kind of impact the use of AI might have on your editorial policies and on newsroom roles, you will gain valuable insights on the challenges you might encounter, and you will reflect on the motivations that should guide the introduction of AI in your workflows and processes. 

News Algorithms: The Impact of Automation and AI on Journalism

A free MOOC taught by Professor Nicholas Diakopoulos of Northwestern University and offered by the Knight Center for Journalism in the Americas at the University of Texas. This course will peel back the mystery around algorithms and AI. You will learn how news algorithms are implemented and deployed in their work.

Hands-on Machine Learning Solutions for Journalists

Free video lessons led by John Keefe and developed by his team at the Quartz AI Studio. They will help you understand when AI might help you, and walk you through a series of example projects tailored for journalists – such as detecting objects in images, sorting documents into piles, and extracting people’s names from a trove of text.

Elements of AI

A free online course developed by Reaktor and the University of Helsinki to demystify AI. Although not focused on journalism, the course offers an excellent introduction, addressing questions such as: How AI might affect your job or your life? What AI really means – and how it’s created? How AI will develop and affect us in the coming years?