CMDA-4654: Intermediate Data Analytics and Machine Learning
Description: A technical analytics course. Covers supervised and unsupervised learning strategies, including regression, generalized linear models, regularization, 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: 24
Average GPA: 3.18 (B+)
Strict A Rate (No A-) : 32.78%
Average Withdrawal Rate: 2.66%
| Robert B Gramacy | 2022 | 41.0% | 34.9% | 15.1% | 2.0% | 4.3% | 2.7% | 3.07 | 7 |
| Christian Lucero | 2024 | 46.9% | 31.3% | 14.9% | 1.3% | 2.4% | 3.2% | 3.19 | 14 |
| Tajbakhsh Sam Davanloo | 2016 | 36.4% | 18.2% | 18.2% | 27.3% | 0.0% | 0.0% | 2.64 | 1 |
| Jyotishka Datta | 2023 | 85.4% | 13.4% | 0.0% | 0.0% | 1.1% | 0.0% | 3.83 | 2 |