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Courses
Spatial Data Science and Applications (DSC 170) & Data Science Approaches to Spatial Analysis (GPEC 447)
Spatial Data Science and Applications (DSC 170) & Data Science Approaches to Spatial Analysis (GPEC 447)
Examples from GRANDE-U are incorporated in two spatial data science courses offered at UC San Diego. In these courses, students learn the fundamentals of online mapping, spatial data management, and spatial data science, with practical experience using Python and Jupyter notebooks. GRANDE-U materials are used to illustrate several concepts in machine learning for spatio-temporal environmental data, including spatial autocorrelation, spatial and temporal leakage, and group k-fold validation.
Machine Learning Applications in Hydrogeology
Machine Learning Applications in Hydrogeology
This course is designed for graduate students and professionals interested in applying machine learning techniques to hydrogeological problems. It includes setting up the computing environment, an introduction to Python programming, and hands-on case studies focused on groundwater modeling and data analysis. All course materials are accessible via the shared link, and the code can be run directly in Google Colab. Users can also clone the files to their own Google Drive for private editing and experimentation.
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