CS 108: DATA SCIENCE ETHICS
University of California, Riverside
4 Units, Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): CS 105 or STAT 107 or CS 171; or consent of instructor. Covers ethics specifically related to data science. Topics include data privacy; data curation and storage; discrimination and bias arising in the machine learning process; statistical topics such as generalization, causality, curse of dimensionality, and sampling bias; data communication; and strategies for conceptualizing, measuring, and mitigating problems in data-driven decision-making. Cross-listed with STAT 108. Credit is awarded for one of the following CS 108, STAT 108, CS 212, or STAT 212.
Average GPA: 3.73
Grade distribution records: 439 students across 6 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 27 | 6.2% |
| A | 259 | 59.0% |
| A- | 78 | 17.8% |
| B+ | 21 | 4.8% |
| B | 17 | 3.9% |
| B- | 9 | 2.1% |
| C+ | 8 | 1.8% |
| C | 4 | 0.9% |
| C- | 4 | 0.9% |
| D+ | 4 | 0.9% |
| D | 2 | 0.5% |
| F | 1 | 0.2% |
| NP | 2 | 0.5% |
| W | 3 | 0.7% |
Based on 439 student grade records across 6 terms and 2 professors.
Instructors
- Analisa Flores 67 students, Average GPA 3.40
- Mariam Salloum 63 students, Average GPA 3.84