GEMS Learning - Introduction to Spatial Data Analysis in Python

Location & Details

Oct. 6, 2023 to Oct. 20, 2023
10:00am to 12:30pm
About This Event: 

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. Through this 3-week introductory course, you will 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. In each 2.5 hour lecture, you will have the opportunity to immediately practice your new skills via hands-on exercises focused on agri-food applications. 

GEMS Learning – Introduction to Spatial Data Analysis in Python

  • Week 1: Introduction to spatial data and mapping in Python
  • Week 2: Basic geocomputation with vector data in Python
  • Week 3: Basic geocomputation with raster data in Python

The course will be delivered via a Jupyter Notebook hosted on the GEMS Informatics Platform. You do not need to have R or RStudio installed on your machine to participate.

Fee: $525 (no fee for U of M affiliated)

This is a three-part course that will take place at the same times on October 6, October 13, and October 20.

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

Scholarships are available (see the link on the registration page). See the full line-up of courses and register