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PHYS 3600ID

Machine Learning for Physics · 3 credits · Fall 2026

This course meets as a lecture plus a lab. Your schedule needs one time from each, and the schedule builder picks them together.

Requirements

P: CST 1201 or equivalent, MAT 1272 or MAT 1372 or MAT 2572 or permission

About this course

Problem solving in physics and astronomy through statistical inference, machine learning algorithms and data mining techniques. Researching and solving problems in different areas of physics using tools such as Bayesian statistics, Monte Carlo sampling, regression and classification algorithms, dimensionality reduction and data cleaning data. Programming assignments use current, flexible languages, such as Python.

Seat status as of Oct 3, 6:31 AM ET. Seats can change between refreshes.

Chill Rank compares professors using Rate My Professors reviews, from Chill to Brutal. What each rank means

D098-LEC Regular
Mon · 10:00 AM - 11:40 AM
Namm N-819
Viviana AcquavivaChill Rank 1 of 5: Chill?★ 5.0(13)Difficulty 2.1/5 · 100% would take again
In PersonOpen
L099-LAB Regular
Wed · 10:00 AM - 11:40 AM
Namm N-819
Viviana AcquavivaChill Rank 1 of 5: Chill?★ 5.0(13)Difficulty 2.1/5 · 100% would take again
In PersonOpen