The course "From first principles to machine learning methods in materials informatics" takes an advanced dive into the intricacies of building Machine Learning models that augment and expand the possibilities of the first-prinicples methods of Quantum Mechanics in atomistic materials simulations. The study materials cover the topics from specifics of architectures of atomistic ML models, through the details of data acquisition and preparation, to training, validation, and application of the models. The course gives practical recipes for the steps to take in building the models and overcoming some of the challenges along the way.Course duration: 15 hours (0,5 ECTS)

Start: June 17th, 2024

The course was developed within the framework of the Project BOOSTalent: Empowering HEIs to Lead in Deep Tech Excellence with Innovative AI and ML for Sustainability, Aerospace, Advanced Materials, and Electronics (EIT HEI Initiative).