Computing and Data Analysis for Environmental Science

Environmental challenges require rigorous data analysis to identify trends, model outcomes, and make informed scientific decisions. This text-based course introduces you to the core principles of computing and data analysis tailored specifically for environmental applications. You will transition from understanding raw field measurements to executing structured data workflows that reveal critical environmental insights. Learn to import, clean, and analyze spatial and temporal datasets while exploring foundational statistical modeling techniques. What you'll learn: Understand core environmental data structures and basic programming logic; Apply descriptive statistics and hypothesis testing to environmental datasets; Clean and pre-process noisy or incomplete field and sensor data; Model environmental systems using regression and basic spatial analysis; Interpret and present data trends through structured data visualization principles; Write clean, reproducible code using modern programming best practices. The course begins with essential terminology and the fundamentals of environmental data before guiding you step-by-step through practical analysis techniques and modeling workflows. This course is designed specifically for beginners, students, and professionals in environmental science or civil engineering with no prior programming experience. Start your journey into environmental data analysis today.