CHE-4404: Machine Learning in Chemical Sciences and Engineering
Description: Development and application of data-driven computational models. Focus on applications in chemical sciences and engineering (e.g., materials discovery, property prediction, anomaly detection, process optimization). Preprocessing, data management and visualization, clustering, classification, and regression algorithms, and common pitfalls and practices in training and evaluation of data-driven models. Pre: 3124
Pathways: N/A
Course Hours: 3 credits
Corequisites: N/A
Crosslist: N/A
Repeatability: N/A
Sections Taught: 1
Average GPA: 3.78 (A)
Strict A Rate (No A-) : 45.49%
Average Withdrawal Rate: 18.18%
| Hongliang Xin | 2022 | 63.7% | 18.2% | 0.0% | 0.0% | 0.0% | 18.2% | 3.78 | 1 |