Artificial Intelligence Concepts

Catalog description

Prerequisites: Graduate standing or Consent of Instructor. This course is an introductory course that presents a survey of AI concepts. The students will learn what AI is and what its applications and limitations are. The course covers search, optimization, constraint satisfaction, game playing, logic, planning, Bayesian networks, Kalman and particle filters, machine learning, hidden Markov modeling, and natural language processing in applied mechanical engineering contexts, such as computer vision, robotics, and intelligent systems. The course offers basic Python-based examples, and elementary-level knowledge of Python is suggested. Shares lecture with MENG 4069, but is graded separately.