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Community Data Science Workshops (Fall 2014)/Reflections: Difference between revisions
Community Data Science Workshops (Fall 2014)/Reflections (view source)
Revision as of 01:03, 27 December 2014
, 9 years agochange mentee to participant
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Once again, quite a large number of people applied were already skilled programmers. We're still not exactly sure why these people are applying because we think that the fact that the workshops are for absolute beginners is very clear. Perhaps people just want more exposure to data science?
Once again, the constraint on scaling the workshop was the number of mentors. Every mentor we added means that the workshop can accommodate four more
One suggestion was allowing
== Morning Lectures ==
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'''How can we support self-directed projects?'''
Can we give
It’s easier to do that if people are pre-clustered.
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- public healtha nd epi data session
We would love to create a session on '''basic statistical analysis in Python''' and at least ten
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* The sticky notes we bought were small and ambiguous color. We should get bright red sticky notes next time.
* Set up/arrange/select the space to facilitate better circulation of mentors.
When mentors can circulate easily things are better for
* We are going to try writing installation instructions that do not rely on Anaconda so people have a fully open source option.
* Once again, not a single person outside of mentors ran GNU/Linux. We should strongly consider how much effort we want to put into maintaining this part of the curriculum.
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'''The spreadsheets session.''' People were modifying the code to build their own dataset and did their own visualizations. At least a few people. That was cool!
'''The MatPlotLib session'''. Most people in the session were deeply lost. The mentors who taught it were not at any of the other sessions and therefore didn’t go in with a good sense of where the
matplot lib
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* Diversity of projects inspires people to do the kinds of things that people can do with this new knowledge.
Otjher ways encourage generative-ness? might include giving
== Budget ==
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'''The ethnographers get the last word:'''
Some observations about the culture of mentoring from a first time mentor: There are some distinct values that came through strongly. There is a clear vision of empowerment through programming. The degree of inclusivity is impressive. The culture of feedback, iteration, and reflection was really surprising such as the amount of effort that goes into improving the materials and the teaching. As is the way that other organizations are able to (and are) using the materials. The way that this is building the community. For example, how
The pragmatism of what is taught demonstrates a clear value. It would be helpful to make sure that all mentors are clear that part of what is expected of them they give pragmatic coaching. That is they should lead
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