Location & Details
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 Regression in Python
March 24, 10:00 a.m. – 12:30 p.m.
The other course in the Accounting for Location in Agriculture in Python series is:
- Introduction to Spatial Data Analysis in Python, February 17, February 24, March 3
Scholarships are available (see the link on the registration page). See the full line-up of courses and register.