Fundamentals of Data Science for Earth and Environmental Systems Science

Course Code: ES0002

 

Course Description:

Modeling, simulation, statistical learning and data science methods are powerful tools for earth and environmental systems sciences. This course will cover the major concepts for building and evaluating models, including fundamentals of statistical and machine learning. Topics covered include (1) basic concepts and tools in data science, (2) statistical thinking, (3) goals and principles of scientific modeling, (4) model development, (5) model calibration and selection, (6) sensitivity analysis, (7) model evaluation, (8) model predictions, (9) results visualization and communication. Students will gain hands-on experience in developing models and simulations (using R programing language).