September 2, 2020

The faculty of MSE’s new Autumn course Data Science and Materials Informatics would like to invite all College of Engineering students to register.  The course prerequisite is knowledge of Python OR another programming language [this is different than what’s listed in the official course description].  Python will be taught in the course to those who don’t know it.

The current course syllabus is attached.  Here are the course and registration details:

MSE 477 (for undergrads) (SLN 23624)

MWF 1:30-2:20 Pacific Time



This is the first course in what will be a three-course sequence of MSE Data Science classes this academic year:

MSE 477 Data Science and Materials Informatics (3)
Introduction to data science approaches and their applications to materials science research. Basic skills in data mining, data processing, and machine learning for materials research topics using Python taught through case studies and other methodologies. Offered: jointly with CHEM 441.

MSE 478 Materials and Device Modeling (3)
Implementation of computational and data science methods in materials science discovery and device modeling to gain physical and statistical insights of materials design. First-principles methods, multiscale simulations, and continuum modeling will be introduced within the framework of active machine learning with application of both computational and data science methods to materials study. Prerequisite: MSE 477/CHEM 441. Offered: jointly with CHEM 442.

MSE 479 Big Data for Materials Science (3)
Introduces the challenges and opportunities of the big data era for materials science and chemistry research. Students will gain basic knowledge and skills of data management using high performance computing, including automated data processing, batch processing, and cloud based computational tools that are suitable for materials science research. Prerequisite: MSE 477/CHEM 441. Offered: jointly with CHEM 443.