AI-related Courses

Computer Science

Artificial Intelligence CSCI151 HM
Credit(s): 3
Instructor(s): Boerkoel, Talvitie
Description: This course presents a general introduction to the field of Artificial Intelligence. It examines the question: What does (will) it take for computers to perform human tasks? It presents a broad introduction to topics such as knowledge representation, search, learning and reasoning under uncertainty. For each topic, it examines real-world applications of core techniques to problems which may include game playing, text classification and visual pattern recognition.
Prerequisite(s): CSCI070 HM and (MATH056 HM or MATH062 HM or BIOL154 HM or MATH151 CM/PO/PZ/SC)

Machine Learning CSCI158 HM
Credit(s): 3
Instructor(s): Montañez, Talvite
Description: Machine learning is concerned with the study and development of systems that learn patterns in data. This course introduces the most common problems in the field and the techniques used to tackle these problems, with a focus on supervised and unsupervised learning. Concepts include mathematical foundations and algorithmic approaches.
Prerequisite(s): CSCI070 HM, MATH073 HM, and (MATH056 HM or MATH062 HM or BIOL154 HM or MATH151 CM/PO/PZ/SC); CSCI151 HM recommended

Natural Language Processing CSCI159 HM
Credit(s): 3
Instructor(s): Medero, Schofield
Description: An introduction to the fundamental concepts and ideas in natural language processing, sometimes called computational linguistics. The goals of the field range from text translation and understanding to enabling humans to converse with robots. We will study language processing starting from the word level to syntactic structure to the semantic meaning of text. Approaches include structured and statistical methods, as well as exploration of current natural language research. Students will build and modify systems and will use large existing corpora for validating their systems.
Prerequisite(s): CSCI081 HM and (MATH056 HM or MATH062 HM or BIOL154 HM or MATH151 CM/PO/PZ/SC)

Engineering

Machine Learning: Theory & Application ENGR208 HM
Credit(s): 3
Instructor(s): Staff
Offered: Fall
Description: An introduction to modern machine learning methods and their application to signals. Students will learn to design, train, and use modern machine learning models. These may include, but are not limited to dense neural networks, convolutional neural networks, and recurrent neural networks.
Prerequisite(s): ENGR101 HM and CSCI060 HM, or permission of instructor. 

Humanities, Social Sciences, and the Arts

AI and Ethics PHIL-179 HM
Credit(s): 3
Instructor(s): Kyle Thompson
Description: AI creates unprecedented opportunities and challenges for human beings seeking to live good lives. If used wisely, AI can benefit many domains of human social life, including science, business, medicine, art, transportation, government, and more. However, if used naively or maliciously, AI can amplify social injustice through algorithmic bias, it can be weaponized by people with harmful political purposes, and it can contribute to a technological culture that undermines human values and self-determination. And when AI is in the driver’s seat—both figuratively and literally in the case of autonomous vehicles—who shoulders the responsibility when things go wrong? Increasingly, humans must grapple with whether to view AI systems as moral agents and patients that deserve rights, moral consideration, or compassion. In this course, students will learn about multiple ethical frameworks before applying them to a variety of case studies and important questions relating to AI. Through reading, writing, and discussion, students will emerge from this course with a deeper appreciation of the landscape of possibilities presented by integrating AI systems into the beautiful messiness of the human world.
Prerequisite(s): Permission of instructor.

HSA10: Star Trek
Credit(s): 3
Instructor(s): David Seitz
This critical inquiry course draws on AI-skeptical themes present in Star Trek, particularly with respect to questions of labor and automation. This might seem counterintuitive, given the association of the show with technological futurism and technological optimism. However Star Trek is far from uniformly keen on those things. The lens of science fiction (sf) studies itself helps enable this approach. The course begins with science fiction scholar Sherryl Vint, who writes that “Social as well as technological change is at stake in sf, which helps us think through whether advances in science and technology are also always advances in civic and social life.”