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: Homeworks (50%), Exam 1 (15%), Exam 2 (15%), Final Exam (20%).
Instructor: Larry Holder , EME 227, 335-6138, firstname.lastname@example.org. Office hours: Tue/Thu 2-3pm, or by appointment.
Yang Hu, email@example.com. Grades even-numbered homeworks. Office hours: Tue 3-5pm in Dana 2.
Samir Sbai, firstname.lastname@example.org. Grades odd-numbered homeworks. Office hours: Tue/Thu 11am-12pm in Sloan 342.