Introduction to Machine Learning for Engineering Research Author: Benjamin Afflerbach Content Type: full course, pre-recorded lectures, slides, jupyter notebooks, and readings Content Length: 10 weeks (1 semester) Content Audience: undergraduate Content Topics: data cleaning, featurization, model assessment, linear models, neural networks, deep learning, computer vision, machine learning, and undergraduate research Last Updated: 2024-10-03
Materials Informatics at the University of Utah (Sparks Group) Author: Taylor Sparks Content Type: Full Course, pdf course notes, example jupyter notebooks, Homework Assignments, and Final Project Content Length: Semester Content Audience: Undergraduate Content Topics: Materials Informatics, Structure-property relationships, Data-driven discovery, Chemical space exploration, Feature engineering, Small datasets, Uncertainty quantification, Ensemble methods, Active learning, Transfer learning, Self-supervised learning, Composition-based feature vector (CBFV), Structure-based features, Crystal structure representations, Graph Neural Networks (GNNs), Message passing, Generative adversarial networks (GANs), Data augmentation, Inverse design, Diffusion models, Periodic lattices, Sparse graphs, Microstructure segmentation, Two-point statistics, Crystal graph neural networks (CGNNs), Machine learning tasks, Reinforcement learning, Pymatgen, Materials databases (ICSD, MP, OQMD), and Two-point statistics Last Updated: 2024-10-04
Basics of Chemoinformatics Author: Logan Ward Content Type: lecture and notebooks Content Length: 1hr Content Audience: graduate-level chemistry Content Topics: fingerprints, descriptors, and QSPR Last Updated: 2024-11-01
UW Madison MSE 461 Data Science In Materials F24 Author: Dane Morgan Content Type: This is a full course with lecture slides, labs, HW, and project guidelines Content Length: Materials for one semester Content Audience: Accessible to any level, UG or Grad Content Topics: machine learning, databases, featurization, neural networks, convolutional neural networks, and worked examples Last Updated: 2025-04-03