CS 252A: DATA ANALYTICS AND EXPLORATION
University of California, Riverside
4 Units, Lecture, 3 hours; research, 3 hours. Prerequisite(s): CS 141, CS 100; STAT 155 or EE 114 or equivalent; graduate standing; or consent of instructor. Covers important algorithms relevant to the lifetime of data from data collection and cleaning to integration, data mining, and analytics. Topics include: sketch algorithms for computing statistics on data streams; mining social graphs including community detection and graph partitioning; Data Science life cycle: techniques on data cleaning, data integration, Exploratory Data Analysis, and visualization. Cross-listed with EE 251A.
Average GPA: 3.67
Grade distribution records: 104 students across 1 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 6 | 5.8% |
| A | 34 | 32.7% |
| A- | 37 | 35.6% |
| B+ | 18 | 17.3% |
| B | 6 | 5.8% |
| B- | 2 | 1.9% |
| C+ | 1 | 1.0% |
Based on 104 student grade records across 1 term and 1 professor.
Instructors
- Mariam Salloum 104 students, Average GPA 3.67