This course covers the study of intelligent agent design and rational decision making. Topics include goal-driven agents, search techniques, optimization, basic problem-solving methods, logic, knowledge-based agents, statistical and probabilistic reasoning, and the basics of machine learning. Special consideration will be given to working with data structures and techniques required for basic model building in Python along with understanding how to work and interact with Large Language Models. Upon completion, students should be able to demonstrate artificial intelligence design concepts.
Requisites:
Take CSC-121; Take previously. Required./>
Total Class Credits:
3 Class Credits: 2 Lab Credits: 3 Clinic Credits: 0
