Four days of lectures and hands-on exercises covering a range of data analysis topics from introduction to python and data pre-processing to advanced machine learning analysis techniques. Example topics include:
Hands-on exercises will include practical use of machine learning tools on real materials experimental data (scalar values, spectra, micrographs, etc.)
Scientists will also demonstrate how they performed recently published research, from loading and preprocessing data to analyzing and visualizing results, all in Jupyter notebooks. Day 4 will include hand-on exercises on how to use the AFLOW database online.