CSCI 373
Artificial Intelligence Spring 2018
Division III Quantative/Formal Reasoning
This is not the current course catalog

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

Class Grid

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