Sara Shamekh teaches courses at both the undergraduate and graduate levels. In all of them, I try to build intuition first and let the formal rigor follow naturally. I believe both are necessary to do good science, and that they reinforce each other. In graduate courses, computation plays a central role, and topics are connected as much as possible to open problems in climate and earth system science.
Graduate
Data-Driven Climate Science
Machine learning and statistical methods applied to climate science, from neural networks to generative models, with hands-on coding throughout.
Climate Dynamics
Physical mechanisms governing Earth's climate system, from atmospheric and oceanic circulation to variability and feedbacks across timescales.
Undergraduate
Ordinary Differential Equations
Introduction to ODEs with emphasis on physical intuition, qualitative methods, and applications in science and engineering.
Introduction to Mathematical ModelingComing next semester
Building and analyzing mathematical models of real-world systems, moving between physical intuition, formal formulation, and computational experimentation.