Are you a GLAMR (gallery, library, archives, museum or recordkeeping) professional or researcher who wants to learn more about AI or machine learning?
Interested in exploring the opportunities for learners with little or no programming knowledge? You’re not alone.
In early 2021, AI4LAM Australia/NZ will support a discussion group considering learning resources and pathways for programming and making the most of developments in AI and machine learning. Dr Susan Ford, history researcher and experienced programmer, will lead a discussion group considering learning options for GLAMR professionals wanting to learn more about AI. Three sessions will consider: what we need to know and why; jargon busting and breaking down barriers; and consider accessible learning resources. Outcomes from these discussions will be shared at AI4LAM webinar in April 2021, drawing upon real experiences to consider how we build our skills.
Three monthly discussion groups will be held online between January 29 and March 26, with a reasonable amount of recommended reading to be completed between sessions.
Click here to sign up or learn more.
Also, are you working on or have you contributed to an AI or ML project using GLAMR collections? AI4LAM AU/NZ is interested in adding Australasian projects to a world-wide register collected and shared by our international colleagues. This register of projects is contributing to a growing ‘AI4LAM Lookbook’, a neat tour of projects big and small from colleagues around the world. If you are working on, or have done, an AI or ML project with GLAMR collections, you can add your details here.
It might be a great opportunity to catch up on any AI4LAM AU/NZ webinars you might have missed, all of which are available online:
https://www.youtube.com/playlist?list=PLgb7wGdsYkJzY37XaIWCd_Jy3XSr4mVbf
Or re-visit any presentations from the 2019 Fantastic Futures conference, which have a wealth of applications of AI in GLAMR organisations to inspire:
https://www.youtube.com/playlist?list=PL_RCUu6isf5EOCmcE2OctSS2y2EMN1xqI
If you’d like to get a headstart on learning, especially if you’re interested in joining the discussion group, have a look at the following short resources:
Machine Learning Algorithms: Khan Academy