Project Summary Advances in biomedical and behavioral data science and machine learning have the potential to promote health equity by aiding in our understanding of the etiology of health disparities. In recognition of the need to foster diversity, improve the quality of biomedical research, and enhance global competitiveness of the U.S. biomedical research workforce, the The Morehouse School of Medicine (MSM) U54 Center for Translational Research in Health Disparities (CTRHD) is investing heavily in biomedical data science and data infrastructure around genomics/multi-omics capacity to support translational projects and enhance informatics education and training opportunities. In this project, we propose a continued collaboration between the Morehouse School of Medicine (MSM-RCMI) and Florida International University’s RCMI (FIU-RCMI) center to: (Aim 1) Refine an existing project-based data science curriculum (Software Carpentry) to include new staple R tools and principles and create new modules for data ethics, data security, and a “Fundamentals for Success” remote synchronous track for learners with lower computer literacy; (Aim 2) Develop a “Train the Trainer” program and train a cohort of data science instructors from MSM and other RCMI partner institutions as well as organize a virtual workshop series for newly trained instructors to teach data science basics and Evaluate learner and instructor progress and experience week over week; (Aim 3) Expand existing partnerships within the RCMI- Coordinating Center and Atlanta University Center Data Science Initiative to disseminate our curriculum and resources related to data science and health disparities via the online Interdisciplinary Health Disparities and Data Science Training collaboratory with remote asynchronous instructional support provided by data science instructors and mentors. The MSM-RCMI and FIU-RCMI have a history of successful collaboration, including our Interdisciplinary Health disparities and data Science trAiNing (IHSAN) program: we trained a pilot cohort of instructors from RCMI centers to teach basic data science using the R programming language. Our program boasts great diversity among our learners (57% female, 33% Black/AA, 29% Hispanic/Latinx) and our trainers (83% female, 25% Black/AA, 33% Hispanic/Latinx). Further, the training we offered shows greater learner confidence week over week with data science in the R programming language applied to health disparities, and the mentored instructors reported greater teaching self-efficacy and confidence after this program. Based on the undeniable success of our pilot training program, we propose to upskill RCMI investigators in data science techniques using R for reproducible data analysis in health disparities research.