CS-5045: 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: 19
Average GPA: 3.77 (A)
Strict A Rate (No A-) : 65.77%
Average Withdrawal Rate: 0.00%
| Liqing Zhang | 2022 | 80.6% | 18.0% | 1.4% | 0.0% | 0.0% | 0.0% | 3.76 | 14 |
| Lenwood S Heath | 2020 | 90.0% | 10.0% | 0.0% | 0.0% | 0.0% | 0.0% | 3.88 | 3 |
| John E Wenskovitch | 2023 | 92.9% | 7.2% | 0.0% | 0.0% | 0.0% | 0.0% | 3.92 | 1 |
| Denis Gracanin | 2011 | 37.5% | 62.5% | 0.0% | 0.0% | 0.0% | 0.0% | 3.49 | 1 |