Geospatial Data Science

3 credits · Nicholas School of Environment

Learn about the foundations of modern geospatial data science - how to analyze vector, raster, and network data in Python & train a basic machine learning model to make predictions. Assignments will be based on real data with analytical methods addressing contemporary environ challenges in the US. Learn about aspects of data science including data acquisition, scalability, & visualization and general principles in project mgmt. Undergrads will conduct a research project. Grad students will complete a final project - including a short research paper. Recommended: some experience with programming and GIS. This is a graduate level version of an undergraduate intro course. Open to grads only.