Jupyter lab tutorial

On May 5 & 6 2021, I took part in the Workshop “Kompetenz Forschungsdatenmanagement” organized by the Max Planck Digital Library. Day 2 featured a full session on “Reproducible Science with Jupyter” with a presentation by Hans Fangohr (slides available here) followed by an interactive hands-on tutorial. In part 1 of the tutorial, I step through a data analysis workflow based on the Johns-Hopkins University CoViD19 dataset from github. Part 2 and 3 are about Bayesian Inference of SIR model parameters, kindly provided by Johannes Zierenberg from MPI Dynamics and Selforganization. All notebooks are available at https://gitlab.gwdg.de/mpievolbio-scicomp/fdm2021/-/blob/master/notebooks or interactively on mybinder.org at https://mybinder.org/v2/git/https%3A%2F%2Fgitlab.gwdg.de%2Fmpievolbio-scicomp%2Ffdm2021.git/HEAD?urlpath=lab.