Introduction to Artificial Intelligence

3 credits

Principles and techniques for automated rational decision-making by machines. Key approaches include search, Markov Decision Processes, graphical models, Bayesian reasoning, reinforcement learning, neural networks, and other topics in artificial intelligence and machine learning. Draws examples from multiple application domains and considers societal consequences of automation and bias. Intended for non-majors. Course overlaps with: CSE 473; CSS 382; and TCSS 435. Prerequisite: CSE 373.