CMDA-4634: Scalable Computing for Computational Modeling and Data Analytics
Description: A focused study of concepts and tools that accelerate computational and data science at scale. Design, analysis, optimization, and modeling of application-driven algorithms suitable for state-of-the-art scalable computing platforms. Software development and engineering for scalable computational science.
Pathways: N/A
Course Hours: 3 credits
Corequisites: N/A
Crosslist: N/A
Repeatability: N/A
Sections Taught: 2
Average GPA: 3.59 (A-)
Strict A Rate (No A-) : 66.15%
Average Withdrawal Rate: 0.00%
| Timothy Warburton | 2023 | 80.8% | 9.1% | 4.5% | 5.5% | 0.0% | 0.0% | 3.59 | 2 |