CS-5046: Computation for the Data Sciences
Description: Covers fundamentals of computer science and background in data sciences needed by graduate students without a computer science background. 5045: Programming language syntax and semantics for data science; abstraction and object-oriented programming; data structures; databases; visualization; ethics and data manipulation. 5046: Software engineering; data preprocessing; and machine learning. Pre: Graduate standing for 5045; 5045 for 5046.
Pathways: N/A
Course Hours: 3 credits
Corequisites: N/A
Crosslist: N/A
Repeatability: N/A
Sections Taught: 11
Average GPA: 3.74 (A)
Strict A Rate (No A-) : 75.45%
Average Withdrawal Rate: 0.00%
| John E Wenskovitch | 2024 | 100.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 4.00 | 1 |
| Liqing Zhang | 2023 | 96.3% | 1.7% | 0.0% | 0.0% | 2.1% | 0.0% | 3.87 | 6 |
| T M Murali | 2007 | 56.3% | 37.5% | 6.3% | 0.0% | 0.0% | 0.0% | 3.55 | 2 |
| Lenwood S Heath | 2017 | 83.4% | 0.0% | 0.0% | 0.0% | 16.7% | 0.0% | 3.28 | 1 |
| Staff Palmisano | 2013 | 80.0% | 10.0% | 10.0% | 0.0% | 0.0% | 0.0% | 3.55 | 1 |