ESPM-88B: Data Science in Ecology and the Environment

This course is a “connector course” that will be open to freshmen enrolled in UC Berkeley’s Foundations of Data Science course (DS-8/Stat-94/CS-94).

Many of the greatest challenges we face today come from understanding and interacting with the natural world: from global climate change to the sudden collapse of fisheries and forests, from the spread of disease and invasive species to the unknown wealth of medical, cultural, and technological value we derive from nature. Advances in satellites and micro-sensors, computation, informatics and the Internet have made available unprecedented amounts of data about the natural world, and with it, new challenges of sifting, processing and synthesizing large and diverse sources of information. In this course, students will apply methods and understanding they gain in the Foundations course to real-world ecological and environmental data sets. Through this hands-on approach, students will learn more about issues in the natural world while also developing the practical skills for working with heterogeneous real-world data encountered in all areas of data science.

ESPM-290: Reproducible and Collaborative Data Science

This is a graduate-level course aimed at students enrolled in UC Berkeley NSF Research Trainee Program Environment and Society: Data Sciences for the 21st Century and other interested students in ecological, environmental or social science programs.