Course description: Artificial intelligence (AI) is the subfield of computer science that studies how to design software that can perform tasks that ordinarily require human intelligence. It is a vast field of research, with many applications, and one of the fastest-growing areas of computer science. This course provides a basic introduction to AI research, techniques, and applications. Topics to be studied include heuristic search; knowledge representation and inference, especially probabilistic inference; planning and decision making; and machine learning. The course provides part of a general education in computer science as well as a foundation for more advanced study of AI.
Class Times and Location: Monday, Wednesday & Friday
10:00 -10:50, Butler Hall 103
Instructor: Eric Hansen
Grader: Rhett Fereday
Textbook (recommended but not required): Artificial
Intelligence: A Modern Approach by Russell & Norvig
Grading:
Prerequisites: CSE 2383 (Data Structures and Analysis of Algorithms) and CSE 2813 (Discrete Structures), both with a grade of "C" or better, and significant programming experience. Familiarity with formal logic, the basics of probability theory, and algorithmic concepts such as graph search, dynamic programming, computational complexity is helpful.
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