Comparative Literature · Fall 2026, Winter 2027, Spring 2027, & Summer 2027

SDSU COMP 536 — Sci Modeling Machine Learning

3.00 units 1 enrollment option

Advanced computational methods and machine learning using Python, implemented from mathematical foundations. Monte Carlo methods, dynamical simulations, Bayesian inference, MCMC, Gaussian processes, neural networks with backpropagation. Students build research-grade implementations, transition to modern frameworks. Develops AI literacy and responsible use. Emphasizes professional software practices and performance optimization.

Course requirements

Prerequisites: MATH 252; MATH 254 or MATH 342A (or equivalent with instructor consent); or Graduate standing

MATH 252; MATH 254 or MATH 342A (or equivalent with instructor consent); or Graduate standing

Spring 2027 enrollment options

Seat status can change

Class #	Format	Status	Seats	Time	Location	Professor	RateMyProfessors
4124 Discussion	In person	Open	0 / 30	Mon/Wed 5:30 PM–6:45 PM	PS 140	Anna Rosen	1.9/5 · 11 reviews Difficulty 3.9 · 9% take again

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