The FAIR (Findable, Accessible, Interoperable, Reusable) principles largely rely on metadata and metadata standards like the Data Documentation Initiative (DDI) for their implementation. More specifically, DDI facilitates the reuse and replicability of data as it provides a comprehensive metadata schema, including information on the data itself, which is important when it comes to assessing data quality and data provenance. DDI is mainly used by a community of people who are familiar with (meta)data management and documentation, and needs to engage more with the less experienced public to increase the uptake of people using the standard and, in turn, create a broader culture of FAIR data practices.In France, the two national open science plans and the recent developments they triggered in the data sharing practices brought DDI to the attention of a lot of « new » data professionals. Even though many DDI training materials (slide decks, recorded webinars) exist, there is a need for « real » beginner training materials. The existent resources are often considered as too abstract, complex and difficult to understand by first-time DDI-users who are not familiar with metadata management in general.The French FAIRwDDI project (work package 2) was designed to fulfil this gap. Specialists from CDSP France and CLOSER UK got together for two week-long sprints and created beginner DDI training materials to showcase at EDDI. The main question they had in mind was: what are the minimum DDI metadata requirements needed to make data reusable? They also wanted to ensure those interacting with the training materials had a foundational understanding of key metadata and DDI concepts. A designer was also a part of the project, helping to make the materials more user-friendly.This talk will present the DDI training material, that will be made available for the community.