Description: Hours: Three hours lecture in the lab per week
Prerequisite: Admission to the Computer Science or Mathematics Graduate Program
Description: This course presents several branches of mathematics that provide computational basis for Artificial Intelligence. The course covers Trees and Search, The Concepts of Predicate Logic, The Theory of Resolution, Nonmonotonic Reasoning, Probability Theory, Bayesian Networks, Fuzziness and Belief Theory, Classifier Systems, Math for Neural Networks, Elements of Statistics, Decision Trees and Optimization.
Units: 3.00
Grading: Letter Grade
| Session | Section | Class # | Type | Days | Time | Location | Instructor | Course Details [Key] |
|---|---|---|---|---|---|---|---|---|
| E1 | 1 | 2116 | LEC | ARR | Online | William Wolfe |
|
Key for Course Detail Icons
| = Course Open |
 = Course Closed |
= Course Details |
 = Textbook Info |
 = General Education |
= Extended University |
 = Service Learning |
= In Person |
 = Asynchronous Online |
 = Synchronous Online |
 = Synchronous/Asynchronous |
 = Blended |
 = No Cost Course Materials |
 = Low Cost Course Materials |