Hi all, A few of us at the Centre for Addiction and Mental Health in Toronto have been teaching a series of Software Carpentry-like workshops[1] (actually some of them are exactly SWC workshops) over two weeks aimed more specifically at researchers in our organization. Much of what we teach is very introductory: what is programming, how to use the linux shell, a very basic intro to R focusing on statistics, a MATLAB and SPSS primer, using Photoshop, etc.. We do also get to a few more advanced topics in some workshops: e.g. doing fMRI analysis in python, using a compute cluster.
We received feedback from learners and instructors that having more cohesion between the lessons would be really helpful to tie things together (currently we have a mixture of lessons with toy examples, more elaborate worked examples, and some with only descriptions/powerpoint), but it's disjointed: there isn't a theme or example dataset running through the workshops. Has anyone tried creating lessons for several different topics around a single example scenario? E.g. using Nelle's data from the Shell lectures[2] to also teach R, Python, Git, etc.. How has it worked out? Is there anything we should be wary of as we wander down this road? Thanks! Jon. [1] e.g. https://camh-scwg.github.io/compucool [2] http://swcarpentry.github.io/shell-novice/01-intro/ _______________________________________________ Discuss mailing list [email protected] http://lists.software-carpentry.org/listinfo/discuss
