Data science and applied statistics courses typically focus on either environmental or social data. This unique course integrates data science and applied statistics from both natural and human systems to examine their relationships and address socio-environmental challenges. Each week, students learn new skills in data science and applied statistics by working on real-world research problems that link environmental and behavioral data to study how people impact ecosystems and how environments influence human behavior. Topics include linear, non-linear, and machine learning regression in R. Weekly assignments guide students through the research process, helping them apply methods, interpret results, and communicate findings.