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.
In this course students will apply methods learned in the Foundations course to explore, pose, and answer key questions using relevant data from the Ecological and Environmental Sciences. In so doing, students will confront the complexity and messiness of real world data, and learn and practice essential tools for capturing, manipulating and sharing data. We will further take advantage of the small class setting provided by the connector to emphasize good workflow and coding practice, collaboration, and help students better master and apply the techniques covered in the Foundation.
Topics will include:
A final project will integrate the concepts and techniques introduced throughout the semester to demonstrate how they work together in one analysis context.