Introduction To Artificial Intelligence

Catalog description

This course covers the fundamental concepts and techniques of artificial intelligence. The topics include intelligent agents and search algorithms (both uninformed and informed search), planning and decision making, supervised and unsupervised machine learning algorithms, and applications of AI in NLP, robotics, computer vision, and other fields. Prerequisite(s): CS 27500 FOR LEVEL UG WITH MIN. GRADE OF C- AND CS 30900 FOR LEVEL UG WITH MIN. GRADE OF C- (MAY BE TAKEN CONCURRENTLY) Course Learning Outcomes 1. Understand the fundamentals of artificial intelligence concepts, techniques, algorithms, applications, and its limitations. 2. Solve problems using python packages like Numpy, Scipy, Pandas and Scikit, etc. 3. Implement seamlessly machine learning and/or other algorithms using python. View Class Schedule