ITCS 6190: Cloud Computing for Data Analysis
University of North Carolina, Charlotte
Introduction to the basic principles of cloud computing for dataintensive applications. Focuses on parallel computing using Google's MapReduce paradigm on Linux clusters, and algorithms for large-scale data analysis applications in web search, information retrieval, computational advertising, and business and scientific data analysis. Students read and present research papers on these topics, and implement programming projects using Hadoop, an open source implementation of Google's MapReduce technology, and related NoSQL technologies for analyzing unstructured data.
Average GPA: 3.85
Grade distribution records: 1,344 students across 22 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A | 1,153 | 85.8% |
| B | 162 | 12.1% |
| C | 20 | 1.5% |
| W | 5 | 0.4% |
Based on 1,344 student grade records across 22 terms and 4 professors.
Instructors
- Angelina Tzacheva 789 students, Average GPA 3.99
- Srinivas Akella 334 students, Average GPA 3.45
- Marco Vieira 149 students, Average GPA 3.90
- Pamela Thompson 72 students, Average GPA 4.00