Benefits of funding or hosting a School of Research Data Science The in-person 2 week long school for early-career researchers corresponds to 3-5% of an MSc degree1 and builds competence in data analysis and security for participants from all disciplines and backgrounds from sciences to humanities. The curriculum can also be offered virtually over 5 or 10 weeks with access to video materials using a Virtual Learning Environment (VLE). 1 We use the European Credit Transfer and Accumulation System (ECTS) credit system to assess the amount of learning for both types of schools. As outlined here, 1 ECTS credit corresponds to 25-30 hours of work. Hence a school corresponds to 2-3 ECTS credits. A full academic year under the ECTS system corresponds to 60 credits and hence the school corresponds to 3-5% of an MSc degree. 2Helpers are often recruited from the local community at the host site or alumni to support schools. Helpers support learners one-on-one if they are stuck installing software, understanding a certain line of code, or any other parts of the learning process. Curriculum topics • Research Data Management (RDM) • Open and Responsible Research • Open authoring and publishing, scholarly identity and reputation, and research impact (Author Carpentry that includes persistent identifiers and licensing, citation, creating reproducible reports) • Information Security • Data Visualisation • Machine Learning • Artificial Neural Networks • Introduction to the Unix shell and Git • Computational Infrastructures Benefits For funders: • The unique curriculum introduces early career researchers to best practices that allow them to comply with funding policies. • By supporting the schools, a funding organisation contributes to capacity building in Research Data Science. For attendees: • Collaborative learning experience. • Learning from internationally renowned instructors. • The materials are suitable for any early-career researcher who is working with data. • Getting to practise skills in hands-on sessions. • The broad range of materials covers not only technical skills such as coding and data analysis but also topics such as RDM that increasingly funders require. • Openly licensed material allows for re-use to further scale capacity building by hosting organisations and attendees. For hosts: • Useful addition to your existing MSc course offer to gain skilled students. • Internationally renowned instructors. • Opportunity for local staff and students to gain further experience as helpers2. • The hosting organisation expands its local and international Research Data Science network. • The hosting organisation can include this activity in any reports that catalogue diversity, equity, and inclusion initiatives. • Openly licensed material allows for re-use to further scale capacity building by hosting organisations and attendees. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101017536. The funding was awarded through the RDA (https://www.rd-alliance.org/) Open Call mechanism (https://eoscfuture-grants.eu/provider/research-data-alliance) based on evaluations of external, independent experts.. This work is licensed under a Creative Commons Attribution 4.0 International License. https://www.datascienceschools.org/ @DataSciSchools Contemporary research – particularly when addressing the most significant, transdisciplinary research challenges – cannot effectively be done without a range of skills relating to data. The range of skills is varied - it includes the use of a range of data platforms and infrastructures, large scale analysis, statistics, visualisation and modelling techniques, coding skills and data annotation as well as research data management and curation, responsible conduct of research and open and reproducible research. We define ‘Research Data Science’ as the ensemble of these skills. Research Data Science skills are relevant to all disciplin