The objective of this course is to provide with the skills to use computational techniques to model behavioral data. Computational modeling is becoming an essential tool to study cognition, and neuroscience. The course will cover all the steps needed to fit computational models to data in a rigorous way. It will provide both theoretical knowledge, as well as hands-on experience (matlab or python), and will include a computational modeling project. In-class examples will focus on reinforcement learning and decision theory models, but the skills are more widely applicable.

The class will be synchronous and in-person.

Undergraduate students are allowed to enroll in the class with permission from the instructor. Please email the instructor with questions.

Repeat Rules

Course is not repeatable for credit.