Jupyter notebooks are an elegant and flexible tool for teaching computational and mathematical aspects
of biomedical informatics and data science. While notebooks can be easily distributed through services
such as GitHub, Gitlab, or Bitbucket, sharing the entire ecosystem (packages, libraries, data, etc.) that
the notebooks require is not trivial. We have previously demonstrated teaching with Jupyter notebooks
using a JupyterHub ecosystem. In this presentation we will present creating on-demand environments
using Kubernates and Binder. These on-demand environments are well suited for outreach and
dissemination efforts. We will demonstrate this environment using NLM and BD2K funded data-science
modules we have created at the University of Utah from the public health informatic and clinical
informatics domains.


Wendy Chapman (Presenter)
University of Utah

Brian Chapman (Presenter)
University of Utah

Mark Keller, University of Utah
Matthew Samore, University of Utah

Presentation Materials:

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