Biological and Artificial Intelligence
PHYSICS 240
Subject & Catalog Number
Course Information
Description
This course provides a foundational overview of the fundamental ideas in computational neuroscience and the study of biological intelligence. At the same time, the course connects the study of brains to the rapid development of ideas in artificial intelligence. Topics covered include the biophysics of computation, Hopfield networks and attractor dynamics, neural networks, machine learning, Bayesian models, theory of learning, deep convolutional and recurrent architectures, generative models, neural coding, control and dynamics of neural activity, and applications to brain–machine interfaces and connectomics.
Course Notes
Physics 240 is also offered as Neuro 240. Students may not take both for credit. This course is primarily intended for graduate students and advanced undergraduates.
Recommended Prep
Required: Prior coding experience (Python or equivalent). Recommended: One college-level calculus course; prior exposure to neuroscience, machine learning, or statistical/physical modeling.
Available for Harvard Cross Registration
NOTE: This course requires additional sections; you will be prompted to choose secondary components during the Add to Cart process
