Activity. (Formerly Social Network Analysis) Students will learn how to analyze available graph-structured data and how to visualize the data. The class will look at the structure of networks (graphs) and how to predict network evolution. Students will learn basic algorithms from graph theory and how to apply them to network analysis. Students will practice applying the knowledge gained to analyze different types of networks, e.g., biological networks. Prerequisite(s): CS 3100. Recommended: CS 4480, or either MATH 1600 or MATH 1620, or equivalent. (Lecture, 2 hours; activity, 1 hour)
| Updated1 | Course Id | Units | Day | Time | Room | Location | Instructor | Additional Course Fees |
Availability2 |
|---|---|---|---|---|---|---|---|---|---|
| 3/26/2026 1:01 PM | CS 4520 002 | 3 |
Arr |
Arr |
HYBRID 001 |
TURLOCK |
Hatem, Ayat |
$0.00 | 14 |
Course Notes
Student must also enroll in CS 4520-001 (LEC) concurrently.
Hybrid Online - Synchronous. In-person class meetings will be on campus at the room, day, and time listed. Online class meetings will be at the day and time listed.