The Association of Public Health Laboratories/International Society for Neonatal Screening 2023 Newborn Screening Symposium will address state, national and international newborn screening, genetic testing and policy issues important to public
A two-day intensive course including seminars and hands-on coding sessions that teaches attendees to build interactive web applications in R using the Shiny package. This training is offered in NYC.
A two-day intensive boot camp of seminars and hands-on analytical sessions to provide an overview of concepts, techniques, and data analysis methods used in studies of the exposome. This training
A two-day intensive course featuring seminars and applied analytical sessions on key concepts, exposure assessment techniques, epidemiologic methods, community engagement/health policy applications, and statistical analytic approaches for conducting solution-driven environmental
A two-day intensive course of seminars and hands-on analytical sessions to provide an approachable and practical overview of concepts, techniques, and data analysis methods used in Bayesian modeling with applications
A two-day workshop for researchers using R, focused on diving into strategies to make research code more efficient, less likely to harbor hidden bugs, and ready to share as a
A two-day intensive combination of seminars and hands-on analytical sessions to provide an overview of the concepts, techniques, packages, data sources, and data analysis methods needed to conduct Mendelian Randomization
A two-day intensive training of seminars and hands-on analytical sessions to provide an overview of environmental mixtures concepts, techniques, and data analysis methods used in health studies. This is an
A two-day intensive course that combines concept-focused seminars with hands-on exercises pairing Python fundamentals with practical data wrangling and analysis. This is an in-person training in NYC. Professionals from any
A two-day workshop focused on skills development in the application of both traditional and machine learning methods in predicting spatial/temporal variations in environmental exposures (e.g., air pollution, temperature, noise) using