To provide a comprehensive introduction to current research methods in artificial intelligence. The course is appropriate both for nonspecialists who wish to acquire a strong grounding in the engineering aspects of computing with real-world data, and as a prerequisite to more advanced courses in artificial intelligence.
An undergraduate course in artificial intelligence.
Modeling structure and uncertainty in real-world data and reasoning with these models, including perception, categorization and learning. Applications to text and web processing, computer vision, speech recognition and language processing, and user interfaces. Planning for risk and reward. Applications to expert systems, medical decision-making, robotics and design.
Midterm and final examinations and occasional readings, problem sets, and programming assignments.