Artifcial Intelligence (CSCI 350)

This course is an introduction to the major concepts and techniques in the field of artificial intelligence (AI). Topics include agents, search, constraint satisfaction, formal logic, optimization, planning, learning, uncertainty, embodiement, and social impact. Course work blends theory with practice. Theory will be covered in lectures and reading assignments. Practice will be through problem sets and a team project that extend your understanding of the computational challenges AI confronts and have you find clever responses to them.  All programming must be in Python. Ultimately, this combination will change forever your ideas about programming and intelligence.

Machine Learning (CSCI 353)

This course is an introduction to the major concepts and techniques in machine learning (ML), a subfield of artificial intelligence. Topics include datasets, evaluation, classification, regression, regularization, support vector machines, decision trees, ensembles, dimensionality reduction, clusttering, and neural networks. Course work blends theory with practice. Theory will be covered in lectures and reading assignments. Practice will be through problem sets and a team project that extend your understanding of the computational challenges ML confronts and have you find clever responses to them. All programming must be in Python couched in Sci-Kit Learn. Ultimately, this combination will change forever your ideas about programming and intelligence.

Readings in Computer Science (CSCI 493.11)

Making the future, or even keeping pace with it, takes knowledge. Both require the ability to read, write, and speak clearly and thoughtfully about science. This course trains students who already have a general fondness for computer science and discovery in what research is all about. Each time it is offered it explores a different theme.

• You will learn to question. Research is about how to ask, and then try to answer, good questions.
• You will learn to ferret out information. A bibliography is a gift from the author to the reader.
• You will learn to teach yourself. When the paper is not enough, other sources will help you understand.
• You will learn to explain. The best way to grasp ideas is to think, write, and speak about them.
• You will become your own best intellectual critic.

This honors seminar is sectioned by topic, for example AI or robotics or security. It is required for the Undergraduate Research Training program and enrollment is only by permission of the instructor. 

Brains, Minds, and Machines (SCI 111)

SCI 111 is an interdisciplinary science course that addresses current knowledge about how human brains, human minds, and artificially intelligent machines think. Students will learn about groundbreaking work that will provide insight into people, the apps they rely on, and the robots in their future. It is highly recommended for students considering any science major, and for students interested in thinking and problem solving. Course material is organized around three essential questions: What is in your head? How does that make you behave? How could we build a machine like that?