STATISTICS, DATA ANALYSIS, AND CODING FO

Students in the Master of Science in Sustainability Science program will encounter a range of scientific problems throughout their Science-specific courses that require a strong working knowledge of computer programming.  This course provides an introduction to scientific programming using Python. Computer coding skills gained in the course will prepare students for coursework in the Master of Science in Sustainability Science program as well as to succeed in a career having a programming component.  Students enrolled in this course will learn through lectures, class discussion, and hands-on exercises that address the following topics:

1. Basics of computer programming, including precision of variables, arrays and data structures, input/output, control flow, and subroutines.
2. Applying Python to read common scientific data formats, including NetCDF for gridded climate and other environmental data.
3. Applying Python for data analysis, with a focus on popular machine learning methods including linear regression, decision trees, neural networks, principal component analysis, and clustering.
4. Applying Python to visualize scientific data through basic X-Y plots as well as images of data fields on a global map.

This course will train students to analyze and model scientific data using Python in order to better understand current and future environments and their interactions with human systems.  By learning analysis and modeling with Python, students will be better able to inform sustainability policy, management, and decision-making.