COVID-19 Update: The Machine Learning Boot Camp will no longer take place in person due to the COVID-19 pandemic. The Boot Camp will instead be a live-stream, remote training that takes place over live, online video on June 8-9, 2020 from 10am EDT – 4pm EDT. Please note this training is not a self-paced, pre-recorded online training. The Machine Learning Boot Camp is a two-day intensive boot camp of seminars combined with hands-on R sessions to provide an overview of concepts, techniques, and data analysis methods with applications in biomedical research. INSTRUCTORS Noah Simon, PhD, Department of Biostatistics, School of Public Health, University of Washington. Yifei Sun, PhD, Department of Biostatistics, Mailman School of Public Health, Columbia University. Cody Chiuzan, PhD, Department of Biostatistics, Mailman School of Public Health, Columbia University. Investigators at all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. PREREQUISITES AND REQUIREMENTS There are three prerequisites/requirements to attend: 1. Each participant must have an introductory background in statistics. 2. Each participant must be familiar with R. The main software used for the workshop will be R/RStudio, therefore we strongly recommend that participants have a basic understanding of this software prior to attending the Training. 3. Each participant is required to bring a personal laptop with R/RStudio installed prior to the first day of the workshop, as all lab sessions will be done on your personal laptop. R is available for free download and installation on Mac, PC, and Linux devices. If you have any specific questions about R and R studio in the context of the Machine Learning Boot Camp, please email us. For more details and to subscribe for updates; email us at Website: Capacity is limited. Paid registration is required to attend.