CSCI 373
Artificial Intelligence Spring 2018
Division III Quantative/Formal Reasoning
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Class Details

Artificial Intelligence (AI) has become part of everyday life, but what is it, and how does it work? This course introduces theories and computational techniques that serve as a foundation for the study of artificial intelligence. Potential topics include the following: Problem solving by search, Logic, Planning, Constraint satisfaction problems, Uncertainty and probabilistic reasoning, Bayesian networks, and Automated Learning.
The Class: Format: lecture/laboratory
Limit: 24
Expected: 24
Class#: 3269
Grading: no pass/fail option, no fifth course option
Requirements/Evaluation: several programming projects in the first half of the semester and a larger project spanning most of the second half of the semester; reading responses and discussion; midterm examination
Extra Info: may not be taken on a pass/fail basis; not available for the fifth course option
Prerequisites: CSCI 136 and (CSCI 256 or permission of instructor)
Enrollment Preferences: current or expected Computer Science majors
Unit Notes: project course
Distributions: Division III Quantative/Formal Reasoning
Attributes: COGS Interdepartmental Electives

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