AM 261Advanced 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.
Prerequisite(s): AM 213A. Enrollment is restricted to graduate students. Undergraduates may enroll by permission of instructor.
- Enroll in lecture and associated discussion section. Taught in conjunction with AM 160.
Find a section and add it to your scheduleLive seat counts, time-conflict checks and the walk from your previous class.
When it runs
Winter 2027Open Winter 2027
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | Asynchronous | — | Staff | Open 0/40 |
Winter 2026Open Winter 2026
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | Mon Wed Fri 1:20pm–2:25pm | Soc Sci 2 071 | A. Chattopadhyay | Open 30/50 |
Who teaches it
| Instructor | Rating | Difficulty | Would take again | Reviews |
|---|---|---|---|---|
| Ashesh Chattopadhyay | 3.3 / 5 | 2.8 / 5 | 70% | 33 |
From RateMyProfessors, which is student-submitted and not a survey. Small review counts move a long way on one bad quarter.
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