CS-5644: Machine Learning with Big Data
Description: Basic principles and techniques for big data analytics, including methods for storing, searching, retrieving, and processing large datasets; introduction to basic machine learning libraries for analyzing large datasets; data visualization; case studies with real-world datasets. Not for graduate credit for degrees for MS and PhD degrees in Computer Science and Applications (CSA); MEng degrees in CSA allowed to receive credit.
Pathways: N/A
Course Hours: 3 credits
Corequisites: N/A
Crosslist: N/A
Repeatability: N/A
Sections Taught: 9
Average GPA: 3.75 (rounds to A-)
Strict A Rate (No A-) : 63.89%
Average Withdrawal Rate: 0.00%
| Patrick J Butler | 2024 | 86.2% | 12.1% | 1.1% | 0.0% | 0.6% | 0.0% | 3.78 | 7 |
| Narendran Ramakrishnan | 2020 | 73.7% | 23.9% | 0.8% | 0.8% | 0.8% | 0.0% | 3.64 | 2 |