Applied Mathematics

AM 261 Advanced Scientific Machine Learning

Advanced scientific machine learning class, where students learn how to build models of real-life systems from data, e.g., fluid, weather/climate, biological processes, ecology, using machine learning tools seamlessly blended with the theories of ordinary differential equations. This course is in-person and includes in-class programming exercises to gain expertise by practice. Taught in conjunction with AM 160. Students cannot receive credit for this course and AM 160. Undergraduate students who are in the SciCAM 4+1 program are strongly encouraged to take AM 261 instead of AM 160.

Requirements

Prerequisite(s): AM 213A. Enrollment is restricted to graduate students. Undergraduates may enroll by permission of instructor.

Credits

5