Thanks very much, awesome resources.
On 6 April 2016 at 15:53, Richard A. O'Keefe <o...@cs.otago.ac.nz> wrote:
> On 6/04/16 4:49 pm, Linda McIver wrote:
> Finally, why Python? If your intention is to teach *data science*,
> there is a case to be made for (shudder, nausea) Excel. The
> R programming language is admittedly somewhat arcane, but
> "R Commander" (http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/)
> should be a lot easier for beginners to cope with.
> I'm not saying that Python is *wrong*, especially not with NumPy,
> SciPy, and so on available, just that it's not *obviously* the best
> choice for teaching *data science*. (For teaching *programming*,
> that's another question.)
A couple of reasons. 1. It is widely used in real data science. 2. nice
clean human-readable syntax (this is where R seems to hit the wall) 3. We
will do some spreadsheet stuff, but they won't all have access to Excel,
and I want them to learn some basic programming as well, in particular for
data extraction/cleaning type tasks that rather stretch excel's
capabilities. I know you can program macros to do most of this stuff, but
hey presto we are suddenly teaching programming in a
less-than-beginner-friendly syntax and system.
The main thing is that I want to teach them real skills that they can
continue to lose. I find this is crucial for motivation. Also I am
astounded by how many of the scientists I collaborate with can't even begin
to contemplate doing anything remotely like this. Even worse, many of them
are outright frightened by computation. I teach at a science school. Most
of the kids will go into science of some form or other. I want them to
develop confidence with computing, and a basic understanding of data
Exploring Life, Parenting and Social Justice:
Computational Science Education: http://computeitsimple.wordpress.com/
Dr Linda McIver
Teacher & Freelance Writer
Buy Fair Trade - Change the world one coffee at a time
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