The rapid advancement of high throughput technologies has generated an enormous amount of heterogeneous data relevant to the life sciences and data science as a whole. This underscores the need to leverage this data to prepare undergraduate students for career opportunities in STEM that may be more data-focused by teaching big data analytical techniques (BDAT). Faculty at teaching-focused institutions such as community colleges, face numerous obstacles when incorporating BDAT in their life sciences curricula including heavy teaching loads, lack of time, resources, and support to develop new curricula. Additionally, bioinformatics software and modules are often written with specific user expertise in mind, making general usage by faculty difficult and time-consuming. Come learn about the NSF funded Consortium for Biological Data Science Education RCN and our planned infrastructure to support faculty in introducing BDAT and curricular supports. Faculty will be able to engage and provide feedback on one module.
