Uncertainty Quantification (UQ) is the science of mathematically quantifying and reducing uncertainty in systems of all types. Students will learn the nature and role of uncertainty in physical, mathematical, and engineering systems along with the basics of probability theory necessary to quantify uncertainty. The course provides an introduction to various sub-topics of UQ including uncertainty propagation, surrogate modeling, reliability analysis, random processes and random fields, and Bayesian inverse UQ methods.
What you'll learn
understand the nature and role of uncertainty in various systems
apply basic probability theory in quantifying uncertainty
execute uncertainty propagation techniques
develop skills in reliability analysis and surrogate modeling
utilize Bayesian inverse methods for uncertainty quantification