Description: An introduction to the field of artificial intelligence including search, knowledge representation, reasoning, uncertainty, learning, and perception. (3 credits)
Student Learning Outcomes: (1) Understand the major areas and challenges of AI, (2) Apply basic AI algorithms to solve problems, and (3) Understand the ethical issues in AI.
Prerequisites: Data Structures (CptS 122), Probability and Statistics (Math 212 or 360).
Textbook: Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Third Edition, Prentice Hall, 2010.
Grading: Six Homeworks (45%), Exam 1 (15%), Exam 2 (15%), Final Exam (25%).
Instructor: Larry Holder , EME 227, 335-6138, email@example.com. Office hours: Wed/Thu 11am-12pm, or by appointment.
Yongjun Chen, Sloan 312, firstname.lastname@example.org. Office hours: Tue 2-3pm, Wed 10-11am.
Selina Akter, EME 136, email@example.com. Office hours: Fri 10-11am.