Orchard View Room, Discovery Building

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/

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/

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/

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/

Get started with core machine learning concepts using Python and Scikit-Learn. This hands-on Carpentries-style workshop covers regression, clustering, ensemble methods, dimensionality reduction (PCA/t-SNE), and a brief intro to neural networks. We’ll also discuss the ethical implications of machine learning in research. Python experience required (e.g., familiarity with pandas, writing functions, for loops, and using libraries). CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2025-07-30-uwmadison-IntrotoML/

Get started with core machine learning concepts using Python and Scikit-Learn. This hands-on Carpentries-style workshop covers regression, clustering, ensemble methods, dimensionality reduction (PCA/t-SNE), and a brief intro to neural networks. We’ll also discuss the ethical implications of machine learning in research. Python experience required (e.g., familiarity with pandas, writing functions, for loops, and using libraries). CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2025-07-30-uwmadison-IntrotoML/

Learn Skills for Research Software Engineering. Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. 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/2025-06-09-uwmadison-reuswc/

Learn Skills for Research Software Engineering. Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. 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/2025-06-09-uwmadison-reuswc/

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/2025-06-02-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/2025-06-02-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/2025-06-02-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/2025-06-02-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/2025-06-02-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/2025-06-02-uwmadison-reudc/