Funded in part by NIH grant 3T34GM118272-05S1, a supplement to grant 5T34GM118272-05, we are excited to launch the initial version of our FAIR training for AI/ML.
FAIR (Findable, Accessible, Interoperable, Reusable) is a growing international standard for enhancing data stewardship.
“The principles emphasise machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data.” go-fair.org
The Practicum AI FAIR training has been piloted with one group of students and we are evaluating feedback as part of our continuous improvement process.
Instructors wishing to use these resources can apply for access to the instructor repositories which contain additional lesson plans and discussion prompts.
