ITCS 3153 - Introduction to Artificial Intelligence

Basic AI-related math fundamentals and AI concepts. Topics include: probability theory and information theory; basic search/problem-solving methods, such as uninformed search, informed search, adversarial search, local search, and constraint satisfaction problem; knowledge representation and reasoning, like propositional logic and inference; probabilistic reasoning such as Bayesian networks, sampling, and decision networks; sequential decision, such as Markov decision processes and reinforcement learning; and machine learning.

Credit Hours: (3)
Prerequisite(s): STAT 2122, MATH 2164, and ITSC 2214, or permission of department.

Schedule of Classes