CS 463 - Artificial Intelligence

5.0 Credits
Principal ideas and developments in artificial intelligence and machine learning. Topics include problem solving and search, game playing, knowledge representation and reasoning, uncertainty, regression, classification, clustering, retrieval, recommended systems, and deep learning. Completion of CS 171 with a grade of 2.5 or higher or instructor permission.
Prerequisite Admission in the Computer Science Bachelors of Science program is required to take this course.
Course-level Learning Objectives (CLOs)
Upon successful completion of this course, students will be able to:

Compare artificial intelligence (AI) with human intelligence and traditional information processing and discuss its strengths and limitations as well as its application to complex and human-centered problems.
Explain the core concepts and algorithms of advanced AI, such as dynamic Bayesian networks, inductive learning, statistical learning, reinforcement learning, deep learning, natural language processing, and robotics.
Apply basic principles, models, and algorithms of AI to recognize, model, and solve problems.
Analyze the structures and algorithms of a selection of techniques related to searching, reasoning, machine learning, and language processing.
Design AI functions and components involved in intelligent systems such as computer games, expert systems, semantic web, information retrieval, machine translation, mobile robots, decision support systems, and intelligent tutoring systems.

Course Typically Offered
Fall