Spatial Regression in Python

GEMS Learning provides modular non-credit digital and data science education for working professionals and students in food, agriculture, and natural resource application areas. Across the curriculum, instructors have built their course content from their own work executing large-scale data science projects to solve agricultural problems. 

Series: Accounting for Location in Agriculture in Python

Would you like to leverage spatial data to start exploring the relationships of agricultural processes across geographies? This course is designed for those who are interested in explicitly accounting for location in their analyses. Learn how to work with spatial data in Python, starting from importing different spatial datasets and creating simple maps, to conducting basic geocomputation on vector and raster data. Each module includes the opportunity to practice your new skills via hands-on exercises focused on agri-food applications. 

GEMS Learning – Spatial Modeling in Python

Is accounting for spatial dependency in your analyses critical to your work? This course is designed for those who want to learn spatial regression and spatial interpolation techniques and model spatial dependency explicitly. Through this course, you will learn about spatial dependency and spatial autocorrelation. The regression portion covers the construction of spatial weight matrices, testing for spatial association and correlation, and building generalized spatial regression models. The interpolation section covers variogram analysis and kriging methods. You will have the opportunity to immediately practice your new skills via hands-on exercises focused on agri-food applications throughout the course.

Fees

Fee: $175 (no fee for U of M affiliated)
This is a two-part course that will take place at the same time on March 11 and 18.
Scholarships are available (see the link on the registration page). See the full line-up of courses and register.

The other course in the Accounting for Location in Agriculture in Python series is:

Introduction to Spatial Data Analysis in Python

Date, time and location:

• Mar. 11, 2024 to Mar. 18, 2024
• 10:00 am to 12:30 pm
• Online