Should have use the github link, not the coursera link. https://github.com/DataScienceSpecialization/courses <https://github.com/DataScienceSpecialization/courses>
Licensing is BY-NC-SA (it seems). https://creativecommons.org/licenses/by-nc-sa/3.0/us/ <https://creativecommons.org/licenses/by-nc-sa/3.0/us/> Sean > On May 24, 2016, at 1:34 PM, Sean Davis <[email protected]> wrote: > > This is a longer set of lessons, but there is plenty of useful stuff here: > > https://www.coursera.org/specializations/jhu-data-science > <https://www.coursera.org/specializations/jhu-data-science> > > Sean > >> On May 24, 2016, at 1:29 PM, Stephanie Labou <[email protected] >> <mailto:[email protected]>> wrote: >> >> Hi all, >> >> >> The economics department at my university is interested in holding a data >> bootcamp for some of their students and I’ve been trying to steer them >> towards Software/Data Carpentry. (I am a newly certified instructor and >> would love to get a workshop under my belt, especially at my home >> institution.) >> >> >> From my discussions with faculty, they don’t want or need to spend time >> going over Excel or SQL (Data Carpentry) and standards of programming >> (Software Carpentry) isn’t the goal either. What they want: “…what is really >> needed is the workflow from data processing to analysis in R. The content >> doesn’t need to be particularly economics focused as long as the data types >> are relevant. For example, we want to improve our students ability to work >> with a range of data types including time stamped data, and strings, in >> addition to standard numeric. Teach them how to write code to clean and >> process data (merge, reshape, etc.) that clearly documents what was done and >> meets standards of reproducibility. A component on visualization, perhaps a >> ggplot2 focus, would also be interesting.” >> >> >> What they’re describing is basically R for reproducible scientific analysis >> <http://swcarpentry.github.io/r-novice-gapminder/>. Which is great! But I’m >> not sure where to go from here – this alone doesn’t make a Software >> Carpentry workshop (although it could easily take two days) and although the >> topics overlap with Data Carpentry, it doesn’t make a Data Carpentry >> workshop either. >> >> >> Has anyone used the R for reproducible scientific analysis/intermediate R >> <http://resbaz.github.io/r-intermediate-gapminder/> as a two-day workshop? >> If so, what did you call it? Can it still somehow fall under the >> Software/Data Carpentry banner? (Also, is there a main contact person >> between the Carpentrys that I can steer the faculty point person towards? I >> would hate to lead them astray, promising a Carpentry workshop when I can’t >> technically call it that…) >> >> >> Any and all feedback/suggestions welcome! >> >> >> Thanks, >> >> >> Stephanie >> >> >> ---- >> >> Stephanie Labou >> >> >> Research Assistant / Data Manager >> >> Center for Environmental Research, Education, and Outreach >> >> Washington State University >> >> _______________________________________________ >> Discuss mailing list >> [email protected] >> <mailto:[email protected]> >> http://lists.software-carpentry.org/listinfo/discuss >
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