GEMS Learning

Are you a field or bench scientist and always wanted to feel more comfortable with your computing skills? These courses are designed for those who have never used the command line, but realize that the responsibilities they have or will soon take on require them to automate tasks. It will teach basic UNIX command-line skills, enable participants to work remotely on more powerful machines, create and run scripts to automate complex workflows, and synchronize your scripts with the larger community with Github.

• Introducing the GEMS platform  + Jupyter Lab
• Demystifying the UNIX command line
• Working Remotely and Scheduling Jobs on MSI’s systems
• Synching your work with the community

Would you like to use R for your data analysis needs? This two hour introductory workshop is designed for those who are new to R and are interested in learning the basics of using R for data analysis. You will learn how to use R on the GEMS platform, starting from installing packages, setting up your workspace, to the basics of R object types. 

• Introduction to Data Analysis with R

Would you like to leverage spatial data to start exploring the relationships of agricultural processes across geographies? Is accounting for spatial dependency in your analyses critical to your work? Or do you need to create a continuous surface of data (i.e., raster) based on a sample point date taken at selected locations?   Learn how to work with spatial data in R, 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.  

• Introduction to spatial data analysis in R
• Spatial regression in R
• Geostatistics and Interpolation in R

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. 

• Introduction to spatial data analysis in Python
• Spatial Regression in Python

Has your research, studies or work required you to examine the geographic distribution of various biological species? This could be for crop protection, forestry, environmental protection, environmental impact assessment, urban and natural landscape design and development, or simply an interest in any given species, whether insects, pathogens or weeds? Then you are at the right place; species distribution models allow us to understand the potential and realized distribution of various species across our landscapes at different scales.

• Introduction to species distribution modeling, concept, rational, review
• Sourcing & curating species occurrence data sets for species distribution models
• Environmental data, variable selection & processing for species distribution models
• Parametrizing, modeling, testing for species distribution models
• Mapping, evaluation and interpretation

Data is everywhere in agriculture, but knowing what to do with it isn't always easy or straightforward. These modules will give you the basic tools for analyzing a decision-making context, evaluating the data needs, collecting or integrating data, and then performing basic analysis and visualizations. 

• Getting started using data to support decisions
• Using simple models to guide decision making

Each term GEMS partners with experts from across the globe to offer a range of specialty courses. Information on Spring 2023 Topic courses coming soon.