Introduction to Bayesian Statistics for Data-Driven Science and Engineering

4 units · Undergraduate upper division (100-199)

Lecture, four hours; outside study, eight hours. Requisites: course M20, Mathematics 33A. Introduction to Bayesian statistics, with focus on development of intuition and implementation through probabilistic programming. Topics include basics of probability and statistics, Bayesian regression, Bayesian model comparison, sampling, Gaussian processes, Bayesian optimization, and uncertainty quantification. Concurrently scheduled with course C234. Letter grading.