MATS5802
MATS 5802 - Applied Machine Learning in Chemical Engineering and Materials Science (3 Cr.)
Chemical Engineering & Materials Science (11093)
TIOT - College of Science and Engineering
Course description
Machine learning is an increasingly prominent tool used by engineers to aid in the design and characterization of materials and molecules. This course will introduce advanced undergraduates and graduate students to fundamental concepts and practical skills that enable the application of machine learning to these problems. These concepts and skills will be contextualized with examples of recent advances at the intersection of chemical engineering, materials science, and machine learning.
Minimum credits
3
Maximum credits
3
Is this course repeatable?
No
Grading basis
AFV - A-F or Audit
Lecture
Requirements
011495
Credit will not be granted if credit has been received for:
02971
Fulfills the writing intensive requirement?
No
Typically offered term(s)
Every Spring