jupyter

Open Science

Learning dev-ops for reproducible research

Jupyterhub Configuration

Notes from configuring Jupyterhub

Early Exploration with Docker & Kubernetes

JupyterHub Day!!

Jupyter for All the Things

Scientific Computation for Research and Teaching with Jupyter Michael Pilosov, University of Colorado Denver Motivation and Qualifiers Love applied math… Hate the learning curve Want to make (computational) math accessible Some familiarity with website design Vague understanding of application architecture Backstory Wanted to embed interactive content into website Difficulty with back-end, lack of understanding Kept seeing some of the same words/phrases Docker, Servers, Databases, Ports, Containers, Volumes, Mounting, Images, Spawning, etc.

Jupyter for All the Things

Scientific Computation for Research and Teaching (with Jupyter) Michael Pilosov, University of Colorado Denver Background Open-source community growing rapidly MOOCs, textbooks Disrupting traditional software stacks no licenses/contracts! Students often feel intimidated by coding installations vary widely Address scientific reproducibility crisis Simplify Setup for Students Get username/password from professor Log in from ANY computer Platform independent “All” software is pre-installed Additional packages can be installed by students work/ folder allows data to persist Computations are performed “in the cloud” better battery life!