COMP 360D
Fall 2019
| Section:
01
|
| This course may be repeated for credit. |
An introduction to creating programs which appear to behave intelligently. Topics will include search algorithms for problem solving, as well as probabilistic reasoning including regression, classification and decision making. Sample topics include Bayesian Networks, basic Neural Networks and Reinforcement Learning. |
|
| Credit: 1 |
Gen Ed Area Dept:
NSM MATH |
| Course Format: Lecture | Grading Mode: Graded |
| Level: UGRD |
Prerequisites: COMP212 AND MATH228 |
|
Fulfills a Requirement for: (COMP) |
|
Past Enrollment Probability: Not Available |
| SECTION 01 |
| Instructor(s): Wolfe,Pippin Times: .M.W.F. 09:50AM-10:40AM; Location: SCIE113; |
| Total Enrollment Limit: 25 | | SR major: 13 | JR major: 9 | | |
| Seats Available: -1 | GRAD: X | SR non-major: 0 | JR non-major: 0 | SO: 3 | FR: X |
| Drop/Add Enrollment Requests | | | | | |
| Total Submitted Requests: 5 | 1st Ranked: 0 | 2nd Ranked: 0 | 3rd Ranked: 0 | 4th Ranked: 0 | Unranked: 5 |
|