Influenced by the practices of social scientists, data journalists seek to create stories that frame social reality through quantitative data analysis. While the use of statistics by journalists is not new, exponential growth in available data and a desire for source material unmediated by political and public-relations framings have seen data journalism increasingly embraced—to varying degrees—by newsrooms, and editors increasingly seek reporters who can think in computational ways. Journalism programs keen to incorporate data journalism in curricula face a unique set of issues, including a lack of scholarship on data journalism education and how to teach it. This article reports on both the pilot of an international postgraduate collaboration in data journalism education in 2015, in which postgraduate students at two universities investigated state-run gambling in Aotearoa–New Zealand, and the introduction of an undergraduate semester-long paper in data journalism at one of the universities. A visiting Fulbright specialist supported both initiatives, helping to develop staff and student data skills, kick-start a joint investigation by students, and lay the groundwork for future international collaborations. Thanks to his visit, New Zealand educators and students were able to seek support from, a global community of journalists and journalism educators working in data journalism. Set against a literature that predicts an increasing role for computational journalism, this article explores the successes and challenges of these cases of experiential journalism education. It explores the complex but not fatal issues of data competency among both instructors and students, collaboration between geographically distinct programs, access to sensitive datasets, and publication of student work.