Inference from Data and Models
MIT OpenCourseWare offers this graduate-level course on extracting information from observational data using kinematical and dynamical models. The syllabus covers estimation theory, inverse methods, and statistical inference techniques applied to problems in atmospheric, oceanic, and planetary sciences, including how to quantify uncertainty and assess what a dataset can and cannot tell you about an underlying physical model. Materials include lecture notes, problem sets, and references drawn from MIT's Department of Earth, Atmospheric, and Planetary Sciences curriculum. The course assumes familiarity with linear algebra and basic probability, and it builds toward applying these inference methods to real geophysical datasets. As with other MIT OpenCourseWare offerings, all materials are free to access and there is no certificate, paid or otherwise, attached to the course.