Orchard View Room, Discovery Building

Fundamental Data Skills Workshop. The goal of this workshop is to provide an introduction to core geospatial data concepts and dive into working with raster/vector data, including how to open, work with, and plot vector and raster-format spatial data in R. Additional topics include working with spatial metadata (extent and coordinate reference systems), reprojecting spatial data, and working with raster time series data. This lesson assumes you have some knowledge of R. CONTACT: facilitator@datascience.wisc.ed URL: https://uw-madison-datascience.github.io/2026-06-01-uwmadison-dc-geospatial/

Fundamental Data Skills Workshop. Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. Participants will be encouraged to help one another and to apply what they have learned to their own research problems. CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2026-06-01-uwmadison-reudc/

Fundamental Data Skills Workshop. The goal of this workshop is to provide an introduction to core geospatial data concepts and dive into working with raster/vector data, including how to open, work with, and plot vector and raster-format spatial data in R. Additional topics include working with spatial metadata (extent and coordinate reference systems), reprojecting spatial data, and working with raster time series data. This lesson assumes you have some knowledge of R. CONTACT: facilitator@datascience.wisc.ed URL: https://uw-madison-datascience.github.io/2026-06-01-uwmadison-dc-geospatial/

Fundamental Data Skills Workshop. Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. Participants will be encouraged to help one another and to apply what they have learned to their own research problems. CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2026-06-01-uwmadison-reudc/

Intro to Image Processing in Python. This hands-on Data Carpentry workshop introduces foundational image processing skills using Python, designed for researchers who want to work more effectively with image-based data. CONTACT: 815-383-3279, sarah.stevens@wisc.edu URL: https://uw-madison-datascience.github.io/2026-05-18-uwmadison-dc/

Intro to Image Processing in Python. This hands-on Data Carpentry workshop introduces foundational image processing skills using Python, designed for researchers who want to work more effectively with image-based data. CONTACT: 815-383-3279, sarah.stevens@wisc.edu URL: https://uw-madison-datascience.github.io/2026-05-18-uwmadison-dc/

Intro to Image Processing in Python. This hands-on Data Carpentry workshop introduces foundational image processing skills using Python, designed for researchers who want to work more effectively with image-based data. CONTACT: 815-383-3279, sarah.stevens@wisc.edu URL: https://uw-madison-datascience.github.io/2026-05-18-uwmadison-dc/

Intro to Image Processing in Python. This hands-on Data Carpentry workshop introduces foundational image processing skills using Python, designed for researchers who want to work more effectively with image-based data. CONTACT: 815-383-3279, sarah.stevens@wisc.edu URL: https://uw-madison-datascience.github.io/2026-05-18-uwmadison-dc/

CONTACT: 815-383-3279, sarah.stevens@wisc.edu URL: https://docs.google.com/forms/d/e/1FAIpQLSdJ5HjYMtIhP5gsz7PMSOlKq4bKglRkBJ3SGJSedMonAGvskg/viewform

Building Better Research Software in R is a pilot workshop. We will be teaching next steps for doing software development as a researcher, after learning R, the Unix shell, and git/GitHub. This workshop includes how to create a project, project reproducible environment, test your software, work with collaborators, write documentation, and more! CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2026-03-30-uwmadison-bbrsr/

Building Better Research Software in R is a pilot workshop. We will be teaching next steps for doing software development as a researcher, after learning R, the Unix shell, and git/GitHub. This workshop includes how to create a project, project reproducible environment, test your software, work with collaborators, write documentation, and more! CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2026-03-30-uwmadison-bbrsr/

Building Better Research Software in R is a pilot workshop. We will be teaching next steps for doing software development as a researcher, after learning R, the Unix shell, and git/GitHub. This workshop includes how to create a project, project reproducible environment, test your software, work with collaborators, write documentation, and more! CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2026-03-30-uwmadison-bbrsr/

Building Better Research Software in R is a pilot workshop. We will be teaching next steps for doing software development as a researcher, after learning R, the Unix shell, and git/GitHub. This workshop includes how to create a project, project reproducible environment, test your software, work with collaborators, write documentation, and more! CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2026-03-30-uwmadison-bbrsr/

Build AI/ML Applications In Teams with Advisor Support. CONTACT: endemann@wisc.edu URL: https://ml-marathon.wisc.edu/

This short course is teaching tools and practices for producing and sharing quality, sustainable and FAIR (Findable, Accessible, Interoperable and Reusable) research software to support open and reproducible research. CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2025-08-25-uwmadison-ReproducibleSoftware/