Introduction to the field of artificial intelligence, which seeks to understand and build intelligent computational systems. Topics include intelligent agents, problem solving and heuristic search, knowledge representation and reasoning, uncertainty and probabilistic reasoning, machine learning, reinforcement learning, and responsible AI.
A lecture course that surveys computational neuroscience, which is a branch of neuroscience that employs mathematical models, theoretical analysis, and abstractions of the brain to understand the principles that govern development, structure, physiology, and cognitive abilities of the nervous system. We will cover both classical (e.g., GLM, LIF, …