Artificial Intelligence. 3 credits, 3 contact hours

Catalog description

Prerequisites: No formal prerequisites - The course assumes proficiency in at least one programming language, preferably Python, and knowledge of topics of CS 506 , DS 637 . This course explores key representations, techniques, and computational models used to develop intelligent systems. Beginning with the historical developments of AI, the course covers problem-solving paradigms such as blind and heuristic search, knowledge representation, logic programming, constraint satisfaction, handling uncertainty, and optimization techniques. The course also examines foundational machine learning approaches, alongside applications in natural language processing, computer vision, and robotics. Additionally, the course addresses ethical considerations in AI, including bias, privacy, and the implications of AI for the workforce and society. Through theoretical study and hands-on implementations, students will gain a solid understanding of AI methodologies and their practical use in solving complex problems.