Fundamentals of Data for Environmental Studies

With the advent of big data and AI, data has become a critical driver in decision making across organizations and domains. Data is used extensively to solve problems in sustainability including risk assessment, trend analysis, environmental modeling, and program management. Data is also a core component of interdisciplinary research that studies relationships between the environment, economics, demographics, public health, etc. In order to tackle these problems, professionals have been under increasing expectations to possess the skills to interpret, communicate, analyze, and process data. The importance of data has necessitated that professionals not only be familiar with data technology, but be able to approach problem solving with the sufficient rigor needed to produce accurate results and conclusions.This course will introduce the fundamentals of data analysis and computer programming. This course is suitable for students with no prior coding experience and will serve as a comprehensive overview of Python basics. Data visualization and interpretation will be taught using Excel. The course will also demonstrate how data analysis is applied in industry using SQL and Power BI Desktop. Advanced statistics and machine learning will not be covered in this course, but students are encouraged to explore those topics in future classes.