MAE 279. Uncertainty Quantification (4 units)
Link to catalog page: https://catalog.ucsd.edu/courses/MAE.html#mae279
Description
This course is an introduction to uncertainty quantification and will cover basic and advanced computational methods to quantify uncertainties in parameters, systems, and simulation. Covers basics in statistical and stochastic modeling, Monte Carlo sampling techniques including variance reduction and importance sampling, sensitivity analysis, Bayes’ theorem and related Bayesian inference methods (variants of Markov chain Monte Carlo).
Prerequisite courses
MAE 279 has no prerequisite courses.
Successor courses
No courses have MAE 279 as a prerequisite.