Large and innovative spatial data are now ubiquitous across science and engineering ranging from the microscale properties of 3D printed materials to the exposure of populations to pollutants to the global views of our planet from satellites. The challenge to statistical science is to adapt methods from geostatistics to these new problems. Large data sets break traditional spatial methods and multivariate spatial data are not well modeled by classical approaches. This course will provide a hands-on and modern introduction to spatial data, followed by methods for large and nonstationary data and models for multivariate processes. It will be taught by active researchers in this area who have contributed to theory, new methods, and maintain software that makes spatial data analysis easy and accessible.