Resources include course material, videos, code repositories, modules, and online textbooks. The resources are organized around concepts of forecasting, basics of R, Python, ecology, and statistics, data sources, data skills, model building, the forecast cycle, applying forecasts, and using decision science or interpreting forecasts as end-users. And the resources are categorized as Introductory, Intermediate, and Advanced. This is a living document that can continue to have new material added. If you there is a resource you see that is missing, use the link on the pdf to access a form to submit new suggestions.
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