PROJECT SUMMARY. The mission of the INCLUDE Data Coordinating Center (INCLUDE DCC) is to accelerate research that benefits individuals with Down syndrome (DS) by facilitating access and analysis of data from cohort studies of people with DS. A key aspect of this mission is to ensure that the INCLUDE Data Hub and Portal and the datasets hosted in this resource are available to a diverse community of researchers. Therefore, to increase diversity, equity, and inclusion in the INCLUDE Project specifically and in the DS research community more broadly, we propose to develop a training program in data sciences for historically under-represented minorities (URMs). Supported by this administrative supplement, we propose to develop an immersive summer course in data sciences known as the Data Science for Diverse Scholars in Down Syndrome Research (DS3). This course will provide training in the basics of generation, identification, and collection of high content multidimensional datasets; their management, analysis, and visualization; as well as development of key professional skills required for the career advancement of diverse trainees. Led by a multidisciplinary teaching team, the DS3 will be developed along the following Specific Aims: Aim 1. To teach students how to perform FAIR research in the INCLUDE Data Hub and beyond. We will teach on the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) and demonstrate the FAIR use of datasets available in the INCLUDE Data Hub and other synergistic public repositories. We will tutor students about where to find datasets, how to frame answerable questions, considerations in using public data, and how to analyze these datasets in a cloud-based environment. Aim 2. To train students in the skills necessary for big data management, analysis, and visualization. Using short-read next-generation sequencing data as a foundational data type, students will learn the basics of high-performance computing skills in real life scenarios. Students will be trained on the integration of -omics data types with clinical metadata, data visualization, and diverse biostatistical tools. Aim 3. To empower diverse trainees with professional skills necessary for career advancement. We will teach on the importance of networking, grantsmanship, and presentation skills. Furthermore, we will hold networking events for these students in which they will meet prominent DS researchers and self-advocates invited as guest speakers. Students will also present on their research projects and practice appropriate scientific discourse in providing and receiving feedback. Altogether, this training program will enhance diversity, equity, and inclusion in the pool of young DS researchers, while also elevating data science literacy to accelerate research that will benefit people with DS.