Course Schedule and Catalog

Department: Materials Science & NanoEng

Meeting: 2:00PM - 2:50PM MWF (11-JAN-2027 - 23-APR-2027) 

Part of Term: Full Term

Grade Mode: Standard Letter

Course Type: Lecture

Language of Instruction: Taught in English

Distribution Group: Distribution Group III

Method of Instruction: Face to Face

Credit Hours: 3

 

Section Max Enrollment: 35

Section Enrolled: 0

Enrollment data as of: 2-NOV-2026 12:17PM

 

 

Final Exam: Scheduled Final Exam-OTR Room

 

Description: Many technologies will not be possible without the understanding and control of matter. Airplanes need to be built with advanced high strength yet lightweight aluminum alloys and your cell phone will not run without the complex transition metal oxides used in the battery. The field focusing on the development and discovery of new Materials: Materials Science has seen a growing use of machine learning and artificial intelligence (AI) approaches. This class will provide an introduction to data-driven approaches in physical science and engineering within the context of materials science. The class will introduce common machine learning and AI approaches (e.g., linear regression, decision trees, neural networks, …) providing general guidelines for their proper use as well as materials science use cases. The class will in parallel introduce important concepts and data sets in materials science as well basic notions of coding in python. Recommended Prerequisite(s): MATH 101/105, Phys 101/111, Chem 121/111