These training materials are part of a five-part course aimed at early career researchers on FAIR Research Data Management (RDM). We share these materials so that research data professionals can reuse them in their instructions or training sessions. The main theme of this course are the FAIR principles: sharing research data that are Findable, Accessible, Interoperable and Reusable.The FAIR RDM course is intended to be flexible and modular: we invite users to (re)use and adapt those parts that are suitable for their audience.Sessions 1-3 of this course are aimed at absolute beginners: that is, those who likely have knowledge of research processes in general but are new to research data management and the FAIR principles. Sessions 4-5 are aimed at an intermediate level: those who have completed the first three modules and/or already have some existing knowledge of FAIR RDM. The training session 'What is FAIR RDM and why should we do it?' was piloted in September 2024 as the first session in the 'FAIR Research Data Management' 5-session course (beginner and intermediate level). The course was developed and piloted as part of the PATTERN project (https://www.pattern-openresearch.eu/). In ‘What is FAIR RDM and why should we do it?’ learners are introduced to the context of FAIR and why there was a need to develop a set of principles to guide data management and sharing. Next, there is an overview of the principles of Findable, Accessible, Interoperable and Reusable and what they mean in relation to research data. There is a focus on the relationship between FAIR, RDM and Open Data, accompanied by a quiz on this topic. Following the lecture/discussion component of the session, learners are presented with an exercise on the FAIRness of the data underlying publications. Finally, there is an introduction to the Project Work for this session. Learners will begin to work on a project ‘case study’, through which it is possible to carry their learning through the entire five-session series. Though learners will take away knowledge that is broadly applicable across the disciplines, there is a focus on discipline specific learning through the presentation of use cases in different domain areas; through the exercises; and by offering discipline-specific choices for project work. Learning Outcomes: By the end of this session, learners will be able to 1. Explain why it is important to share data 2. Paraphrase the FAIR principles 3. Explain why the FAIR principles were developed 4. Describe the relevance of FAIR and their benefits 5. Outline the relationship between FAIR, Managed Data, and Open Data 6. Begin to identify some features of FAIR data out in the world Project work: An important component of these training sessions was project work that was conducted on the Projects platform (https://pattern.projects.directory/), which you will see references to throughout the slideshows in this series. We asked learners to do some exercises that are based on real research projects that produced and archived data some time in the past. Eight 'use cases' were created, and participants chose one that mached their interests to work on for the duration of the whole course. From the first session onwards, they then worked on these 'use cases' in the Projects platform, with regular 'check ins' with other learners during the live training sessions. The eight use cases have been uploaded to Zenodo separately. File overview:20240903_PATTERN_FAIR_RDM_Session1_Slides: The central slideshow for this 2.5 hour training session20240903_FAIR_RDM_Session1_Quiz: The quiz questions for a quix that was presented using Particify 20240903_FAIR_RDM_Session1_Exercise: a group exercise that was completed by learners during the workshop20240903_PATTERN_FAIR_RDM_Session1_SessionPlan: the document that we created to plan and manage the training session, which we believe will be useful for potential reusers of the content Slideshows are uploaded in .pptx and .pdf format and text documents are uploaded in both .docx and .pdf Related records: Session 1: 10.5281/zenodo.15310232 Session 2: 10.5281/zenodo.15310356 Session 3: 10.5281/zenodo.15310456 Session 4: 10.5281/zenodo.15310506 Session 5: 10.5281/zenodo.15310556 FAIR RDM Use Cases: 10.5281/zenodo.15316306