Artificial Intelligence Complete Lectures (01-23)

Prof. Patrick Henry Winston introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. Upon completion of this course, students should be able to develop intelligent systems by assembling solutions to concrete computational problems; understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering; and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective.

Artificial Intelligence Lectures (01-13) - Barbara Hecker, PhD

Artificial Intelligence course introduces the foundation of simulating or crating intelligence from a computational point of view. It covers the techniques of reduction, reasoning, problem solving, knowledge representation, and machine learning. In addition, it covers applications of decision trees, neural Networks, support vector machines and other learning paradigms. Barbara Hecker, J.D., Ph.D. Barbara is an entrepreneur with a passion for teaching. She’s been a Department Chair, Chief Academic Officer and

The Future of Robotics and Artificial Intelligence

Andrew Ng (Stanford University) is building robots to improve the lives of millions. From autonomous helicopters to robotic perception, Ng’s research in machine learning and artificial intelligence could result one day in a robot that can clean your house.