The National Institute for Computer-Assisted Reporting, a project of Investigative Reporters and Editors, launched in 1989 to train reporters around the world on how to use data as part of broader investigations. In addition to “boot camps” and in-office training, NICAR offers a data library, practice data sets, and hosts the original annual conference on computer-assisted reporting. IRE also publishes the popular book, Computer-Assisted Reporting: A Practical Guide.
The Center for Investigative Journalism published a manual on data journalism “for all journalists who want to master the art of interrogating and questioning numbers competently.” CIJ also provides a slew of additional books, guides and video resources on aspects of data journalism.
DataViz.tools is “a curated guide to the best tools, resources and technologies for data visualization,” with 21 categories that include mining, cleaning, scraping, and interactive story-telling.
The International Consortium of Investigative Journalists provides a selection of video tutorials on basic Excel functions, as well as how to background a person or company, or find federal court documents in the U.S.
The Investigative Dashboard lists tools for data mining, visualization and social network analysis. Google search your tool of choice and you’ll surely find tutorials on how to begin.
The Data Journalism Handbook is an international, collaborative effort involving dozens of data journalism experts. The free guide is available for download in English, French, Georgian, Russian, and Spanish.
The Open Data Handbook discusses the legal, social and technical aspects of open data, with case studies and handy tips.
Codementor offers online tutorials for a fee to learn programmes, which are widely used in newsrooms, such as Ruby on Rails and Python from scratch through code mentors. There are also free useful guides and tips.
KDnuggets offers a wide variety of tutorials focusing on data mining, analytics and data science, including 3 Viable Ways to Extract Data from the Open Web, 4 lessons for Brilliant Data Visualisation, Mining Twitter Data with Python and Text Mining 101:Topic Modeling.