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Subject offerings of new and developing areas of knowledge in aerospace engineering intended to augment the existing curriculum. See Class Schedule or department course information for topics and prerequisite. Course Information: 1 to 4 undergraduate hours. 1 to 4 graduate hours. May be repeated in the same or separate terms if topics vary to a maximum of 9 undergraduate hours or 12 graduate hours.

Room 403A Engineering Hall 3 hours Undergraduates, 4 hours Graduates. Topic: Data-Driven Modeling and Optimization covers advanced topics in the development of probabilistic models for use in analyzing and optimizing aerospace systems. Topics covered include Bayesian inference, Markov decision processes, Monte Carlo methods, adaptive differential evolution, and uncertainty quantification via surrogate modeling and response surface evaluation. Pre-Requisites: AE 498 (Computational Methods for Systems Engineering) or AE 462; SE 413