CS-5834: Introduction to Urban Computing
Description: Computational approaches to address urban challenges; sensor network testbeds; algorithms for storing, processing, and mining data from urban settings; communicating patterns to decision makers; special focus on epidemiology, sustainability, transportation, social science, urban economics; case studies with applications. Pre: Graduate Standing.
Pathways: N/A
Course Hours: 3 credits
Corequisites: N/A
Crosslist: N/A
Repeatability: N/A
Sections Taught: 13
Average GPA: 3.60 (rounds to A-)
Strict A Rate (No A-) : 38.05%
Average Withdrawal Rate: 0.00%
| Narendran Ramakrishnan | 2024 | 60.3% | 37.7% | 2.0% | 0.0% | 0.0% | 0.0% | 3.56 | 11 |
| Bodicherla A Prakash | 2019 | 87.2% | 12.8% | 0.0% | 0.0% | 0.0% | 0.0% | 3.79 | 2 |