Data curation is the process of making data understandable and reusable for publication within a data repository. It can be multifaceted and complex based on the types of data you are curating and the expertise of the curator; and with evolving data sharing practices and standards, ensuring data curators and stewards have access to high-quality instruction on specific data types is essential for supporting the goals of data sharing. Duke University, in collaboration with members of the Data Curation Network (DCN), received an Institute of Museum and Library Services (IMLS) grant [re-252343-ols-22] to support the development of specialized curriculum for data curation training for academic library and archives staff. The project drew together data curators and information professionals to create in-depth training resources for four specialized data types: geospatial data, scientific images, code, and simulations. Building upon the CURATE(D) workflow, the project employed a community-driven cohort approach to develop the new curriculum materials, which were piloted at a 2-day in-person workshop in October 2023. In this presentation we will discuss how this curriculum complements existing DCN training initiatives, the approach to curriculum development, the core content that was developed, plans for dissemination, and reflections on the project.