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Data science methods provide an exciting opportunity to significantly improve the rigor of rehabilitation research by increasing the reproducibility and replicability of research. Data science methods, which rely on computer programming skills for data intake, management, storage, and analysis, can increase reproducibility, but clinical and basic rehabilitation researchers may have challenges adopting these practices due to a lack fundamental training in computer programming. The proposed Reproducible Rehabilitation (ReproRehab) research education program will build a sustainable national workforce of rehabilitation researchers equipped with basic data science skills by: (1) implementing an innovative, hands-on bootcamp for rehabilitation researchers to learn beginning data science skills and integrate them into their own research, (2) employing a train-the-trainer model to rapidly increase capacity for data science and training of data science in the rehabilitation research community, and (3) broadly disseminating data science resources curated specifically for rehabilitation researchers through a publicly accessible web portal.