All students must meet the Requirements for Certificate of Graduate Study.
Overview
The aim of the Certificate of Graduate Study (CGS) in Data Analytics for Water Resources program is to educate students on understanding and developing advanced methods (e.g., physics- and process-based modeling, statistical, machine learning, deep learning and data visualization methods) to address critical water resources challenges such as: Drinking water treatment and access, Recovery and treatment of wastewater, Surface and groundwater management, and Adaptation to climate change and other hazards.
Specific Requirements
Minimum Degree Requirements
The CGS in Data Analytics for Water Resources requires 12 credits (four courses). Two of those courses are the core courses that all students must take, while the other two courses can be taken from a list of electives. Students must maintain a 3.0 average in these courses to receive the CGS.
| Requirement Description | Credits | |
|---|---|---|
| Required Core Coursework (6 credits): | ||
| STAT 5870 | Data Science I | 3 |
| CEE 6610 | Data Analytics Water Resources | 3 |
| Electives (6 credits, at least 3 of which must be from an Applications Category) | ||
| Applications | ||
| Phys/Chem Proc Water/Wstwater | ||
| Principles of Hydrology | ||
| Advanced Hydrology | ||
| Groundwater Hydrolo & Modeling | ||
| Applied River Engineering | ||
| Climate Change Impacts | ||
| Gr Geochem of Natural Waters | ||
| Advanced Fluid Dynamics | ||
| Gr Geochem of Natural Waters | ||
| Gr Geomaterial Analysis | ||
| Topics in Envt & Surface Geo | ||
| Skills | ||
| Bayesian Statistics | ||
| Data Science II | ||
| Uncertainty & Risk in Eng Sys | ||
| Appld Artificial Neural Ntwrks | ||
| Applied Geostatistics | ||
| Advanced Machine Learning | ||
| Evolutionary Computation | ||
| Deep Learning | ||
| Data Vis & Communication | ||
| Computational Biology | ||
| Data Vis & Communication | ||
| Geospatial Computation | ||