Online
Dec 2-4, 2024
9:00 a.m. - 1:00 p.m.
Instructors: Anna Meyer, Rheeya Uppaal, Chris Endemann
Helpers: Anna Meyer, Chris Endemann, Rheeya Uppaal, Gongbo Sun
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This lesson equips participants with trustworthy AI/ML practices, emphasizing fairness, explainability, reproducibility, accountability, and safety across three general data/model modalities: structured data (tabular), natural language processing (NLP), and computer vision. Participants will learn to evaluate and enhance the trustworthiness and reliability of models in each modality. Additionally, they will explore how to integrate these principles into future models, bridging ethical practices with practical applications in their research.
This is a pilot workshop, testing out a lesson that is still under development. The lesson authors would appreciate any feedback you can give them about the lesson content and suggestions for how it could be further improved.
Who: The course is aimed at graduate students and other researchers at UW Madison. Participants must have experience using Python and a basic understanding of machine learning (e.g., familiar with the concepts like train/test split and cross-validation) and should have trained at least one model in the past. Prior experience training neural networks is recommended to get the most out of this workshop.
Where: This training will take place online. The instructors will provide you with the information you will need to connect to this meeting.
When: Dec 2-4, 2024; 9:00 a.m. - 1:00 p.m. Add to your Google Calendar.
Requirements: Participants must have access to a computer with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).
Accessibility: We are committed to making this workshop accessible to everybody.
We are dedicated to providing a positive and accessible learning environment for all. We do not require participants to provide documentation of disabilities or disclose any unnecessary personal information. However, we do want to help create an inclusive, accessible experience for all participants. We encourage you to share any information that would be helpful to make your Carpentries experience accessible. To request an accommodation for this workshop, please fill out the accommodation request form. If you have questions or need assistance with the accommodation form please email us.
Glosario is a multilingual glossary for computing and data science terms. The glossary helps learners attend workshops and use our lessons to make sense of computational and programming jargon written in English by offering it in their native language. Translating data science terms also provides a teaching tool for Carpentries Instructors to reduce barriers for their learners.
Contact: Please email facilitator@datascience.wisc.edu for more information.
Roles: To learn more about the roles at the workshop (who will be doing what), refer to our Workshop FAQ.
Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
The lesson taught in this workshop is being piloted and a precise schedule is yet to be established. The workshop will include regular breaks. Please contact the workshop organisers if you would like more information about the planned schedule.
To participate in the workshop, you will need access to software as described below. In addition, you will need an up-to-date web browser.
We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.
If you haven't used Zoom before, go to the official website to download and install the Zoom client for your computer.
Like other Carpentries workshops, you will be learning by "coding along" with the Instructors. To do this, you will need to have both the window for the tool you will be learning about (a terminal, RStudio, your web browser, etc..) and the window for the Zoom video conference client open. In order to see both at once, we recommend using one of the following set up options:
Follow the setup directions on the <a href=”https://carpentries-incubator.github.io/fair-explainable-ml/index.html”>the workshop website</a>