Lately, I’ve been thinking about a way to help people keep learning & practicing their coding skills long term; my new project, Mozilla Study Groups, are what I came up with, and I wanted to ping the Seattle community to see if people would be interested in trying this out locally.
The idea is to have a casual meetup, maybe 1-2 hours anywhere from weekly to monthly, where people can come and share skills in some guided demos of the code and packages they use in their research, ask each other questions, find out what each other are working on, and just generally have a place to come talk and learn about coding for research.
I’ve made a few assets to support this (all still works in progress, feedback very welcome):
– Study Group Handbook, a how-to guide for organizing these meetup groups: http://mozillascience.github.io/studyGroupHandbook/
– Study Group Website Kit, a forkable, quick to set up website to list events for your group: https://github.com/mozillascience/studyGroup
– Study Group Lessons, a collection of short lessons from past meetups, intended for recirculation: https://github.com/mozillascience/studyGroupLessons
The pilot in Vancouver is a big hit, check out their website: http://minisciencegirl.github.io/studyGroup/ .
Sound interesting? These Study Groups work best when the community gets together to organize; if you’re interested in giving this a go, I’d be happy to help out and maybe scoot down from Vancouver to assist in getting started; let me know!
Mozilla Science Lab
Tag Archives: code
As I was saying in my last post, I’ve been getting interested in actually running Markov Chain Monte Carlo algorithms, instead of trying to prove things about their asymptotic performance. It seems like the “stats” way to do this is to use R and WinBUGS, but I’ve always thought that R programming looks messy. Python is easier on my eyes.
So, it’s my good fortune that PyMC exists. This means I don’t need to do any hard work, like coding a Gibbs sampler or learning R. Let me show you.