What is it about?
As biomedical data grows due to technological advancements, it's becoming more important for researchers to acquire the knowledge and skills necessary to analyze complex data. This is particularly difficult due to the need for short, specific training that can be applied immediately while research continues. The challenge is to create training that combines the practical with the conceptual. To meet this challenge, this article presents nine simple strategies for identifying critical training needs, curating materials to meet these needs, and balancing the conceptual with the practical to produce effective training efficiently.
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Why is it important?
By learning data science skills, researchers can use big biomedical data to make new discoveries. Unfortunately, many researchers worldwide lack the necessary data science expertise which limits their research progress. These nine simple ways to create and deliver training can help biomedical researchers at the cutting edge of data science.
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This page is a summary of: Nine quick tips for efficient bioinformatics curriculum development and training, PLoS Computational Biology, July 2020, PLOS, DOI: 10.1371/journal.pcbi.1008007.
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