The course explores how generative AI can be used as a tool for applied environmental inquiry, design, and communication. Students critically examine the scientific, ethical, and environmental foundations of AI while developing hands-on skills to apply these tools to real-world environmental challenges. The course emphasizes iterative learning, teamwork, and reflection on how digital technologies can serve environmental and societal well-being. No prerequisites or coding experience are required.

This course uses modern Bayesian statistical modeling approaches to analyze ecological and environmental data, with an emphasis on applied hierarchical models. This course will focus on models that are used to examine population and community dynamics, spatial patterns, species abundance and diversity, community organization, metapopulations, and landscape processes. To be successful in the course students should havetaken a course in statistics and have working knowledge of the R programming language.