Data Science and Machine Learning are seen as the “Forth Paradigm” in Materials Science and are reshaping the research direction in many areas. In this training,  the students/participants will gain an overview and obtain hand-on experience on the most relevant machine learning algorithms for theoretical simulations, experimental characterization, and in general statistical analysis in materials science. The participants will work with established packages within Python to develop their own simple machine learning based programs, and are going to tackle a challenging project. Though exemplary datasets, the participants will practice to apply appropriate methods to basic materials science problems, in particular Machine Learning assisted image segmentation, Machine-learning interatomic potentials, microstructure-property correlation analysis, and data-driven multiscale modeling.