CSC 114 Artificial Intelligence I

Lecture: 2 Lab: 3 Clinic: 0 Credits: 3

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. Upon completion, students should be able to demonstrate artificial intelligence design concepts.

Course is typically offered in Spring.
Student Learning Outcomes (SLOs)
At the completion of the course students should be able to do the following:

Apply search and optimization techniques to intelligent agents.
Implement reasoning systems using logic, knowledge-based approaches, and probabilistic methods in intelligent systems.
Evaluate machine learning models within intelligent agents with foundation principles in artificial intelligence.