A study of ethical issues that arise with the adoption of artificial intelligence technologies. This course will help students understand the technologies involved, and the effects they have on society and help them develop possibilities for the resolution of problems that may arise.

An introduction to artificial intelligence as a human endeavor. Presents foundational concepts and techniques of AI, discusses current applications as well as risks and benefits of AI-based technologies, and provides hands on experience using contemporary tools.

An introduction to artificial intelligence as a human endeavor. Presents foundational concepts and techniques of AI, discusses current applications as well as risks and benefits of AI-based technologies, and provides hands-on experience using contemporary tools.

Interdisciplinary study of mind and intelligent activity that forms cognitive sciences. Contributions of psychology, philosophy, linguistics, biology, anthropology, computer science, and education toward uncovering important aspects of the mind and intelligent activity are discussed.

Interdisciplinary study of mind and intelligent activity that forms cognitive sciences. Contributions of psychology, philosophy, linguistics, biology, anthropology, computer science, and education toward uncovering important aspects of the mind and intelligent activity are discussed.

Interdisciplinary study of mind and intelligent activity that forms cognitive sciences. Contributions of psychology, philosophy, linguistics, biology, anthropology, computer science, and education toward uncovering important aspects of the mind and intelligent activity are discussed.

AI-based machines are making life-and-death decisions out in the world and can lead to additional bias and injustice in society. Examination of ethical issues and obligations related to AI. Topics include politics of technology, data collection and mining, algorithm creation and transparency, and the use and future of AI.

Introduction to the hardware and software involved in autonomous mobile robotics. Course content emphasizes the mathematical and statistical models related to robotic perception and motion, associated algorithms, and their programming in computer- simulated environments. Course structure involves classroom instruction, written and programming assignments, and exams.

Programming in LISP and PROLOG, with emphasis on artificial intelligence techniques. Other languages used for artificial intelligence work will be presented more briefly.

Machine learning is changing how we study and understand our world. This course serves as an introduction to the foundations and basic approaches of Machine Learning and their applications. Students will use software and data tools to learn how they can be used to identify complicated patterns in data and to solve real-world problems.

Machine learning is changing how we study and understand our world. This course serves as an introduction to the foundations and basic approaches of Machine Learning and their applications. Students will use software and data tools to learn how they can be used to identify complicated patterns in data and to solve real-world problems.

Reinforcement learning studies methods for learning to act optimally based on the reward or punishment over time. Such machine learning is useful when we wish to learn high-quality behavior under uncertainty and the only data are reward signals. Introduces classical and modern methods in single- and multi-agent settings.