Dive into the innovative field of machine learning in atomistic materials science with this intermediate-level online course. Designed for undergraduate and graduate students in materials science and mechanical engineering, the course explores how machine learning enhances materials modeling, addressing the limitations of traditional methods like density functional theory. Participants will learn to analyze atomistic data, build linear models, and train machine learning interatomic potentials using advanced frameworks and tools.The 15-hour course, delivered in English via Zoom, combines live lectures with self-paced study through video and text materials. Basic knowledge of machine learning, atomistic modeling, and Python programming is required. Successful participants earn a certificate with 0.5 ECTS credits. Offered by Kyiv Academic University, the course is free and led by Dr. Oleksandr Vasiliev, an expert in applied mathematics and computational materials science.
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