CS-4654: Intermediate Data Analytics and Machine Learning
Description: A technical analytics course. Covers supervised and unsupervised learning strategies, including regression, generalized linear models, regulations, dimension reduction methods, tree-based methods for classification, and clustering. Upper-level analytical methods shown in practice: e.g., advanced naive Bayes and neural networks.
Pathways: N/A
Course Hours: 3 credits
Sections Taught: 4
Average GPA: 3.57 (rounds to A-)
Strict A Rate (No A-) : 38.75%
Average Withdrawal Rate: 0.00%
| Christian Lucero | 2024 | 48.3% | 51.7% | 0.0% | 0.0% | 0.0% | 0.0% | 3.55 | 3 |
| Jyotishka Datta | 2023 | 75.0% | 12.5% | 12.5% | 0.0% | 0.0% | 0.0% | 3.63 | 1 |