With the new Data Science Co-Learning being established and after talking to organizers of the Python and Ruby Co-Learnings (@andreas @haiko @mamhoff) an idea came up, to re-shape the scope of some of our Co-Learnings rather by technical topic than by language:
- Backend: Everything around server-side web applications, APIs, servers, databases, ops, any language
- Data Science: Data analasys, visualization, Machine Learning, AI, probably mostly Python, R, …
Frontend already works that way. At the Python Co-Learning, despite offering some web develpment expertise, most participants are doing data-related topics. In the Data Science Co-Learning, most people work with Python. Ruby Co-Learners exclusively do web application development and are also interested in server operations. So the idea would be to merge Python and Ruby into Backend and Data. Rust Hack and Learn and NodeSchool should probably stay as they are. I’m not sure about the Go Co-Learning.
Now, this sounds like a good idea to me and it has worked well for the Web Frontend Co-Learning for years. Still, moving things around causes friction and might not help much.
I wonder what influence on participant attraction it has to have a language name in the event title. Does it attract more experts or beginners? And would the topics of a Backend Co-Learning be too wide-spread (from NodeJS to Java Spring, from Rails to Docker) to have good collaboration? (The Web Frontend Co-Learning sometimes has this with too many frontend frameworks, but we also enjoy the diversity.) Or should it focus on a bunch of core topics?
I would love to discuss this with all of you, organizers, but also participants!