Materials Informatics for Materials Science and Engineering

3 Credits

This course will introduce students to the tools used in materials informatics and modern data science as applied to problems in materials science and engineering. Course topics will include: data wrangling, clustering methods, principal component analysis, genetic algorithms, decision trees, random forests and neural networks. A laboratory component will permit students to apply tools to selected problems and develop computer programming skills. Prerequisites: MAT 033 and MATH 231 and ENGR 010