Developing a Carpentries-style Machine Learning workshop
Jens Brinkmann1, Mike Laverick1 1The University of Auckland – Centre for eResearch, Auckland, Auckland, New Zealand
Abstract
In late 2022 the Centre for eResearch, University of Auckland, received internal funding to develop a researcher skills offering to support the increased application of machine learning (ML) across the research community, especially higher degree researchers.
This resulted in three main tasks: i) leveraging existing Carpentries lessons and teaching
style to develop a ML workshop to enable participants with no prior experience in coding or ML techniques to use ML algorithms after ~20 hours of instruction; ii) testing and improving the delivery of the ML workshop over two cohorts of ~25 attendees in 2023; and iii) informing future delivery of sustainable ML skills offerings.
As a result, relevant Carpentries lessons were identified, evaluated, and adapted, and testing led to the decision to streamline software installation – Google Colab over a local Python installation. Participant engagement during the workshop and feedback in the post-workshop survey was positive and provided directions for improvements to the organisation (e.g., more scheduled breaks, delivery over a wider timeframe), content (e.g., less Python), and instructor delivery. Several adjustments are planned for the second iteration of the workshop (September 2023) based on participant, instructor, and helper feedback. Instructors are increasingly collaborating with peers to co-teach or assist with ML skills offerings being delivered to the Aotearoa NZ research community. Lastly, adjusted lessons will be fed back to the Carpentries community and potentially used in our 2024 programme of digital research skills offerings.
Biography
Jens is passionate about learning how things work and teaching. After working as a consultant in engineering roles in several countries, he came to the University of Auckland for a PhD. After completing his PhD, he went on to teach Automotive Engineering for a year at Unitec. At the Centre for eResearch (CeR), he aims to provide the same high level of support to researchers and staff members that he received from CeR during his own PhD. Currently, he works with AR and VR equipment and explores and teaches Machine Learning (ML) and as wlel as other workshops.