Recommendations for intro to python+programming lecture to Humanities MA students

[Andrew Z]

Goktug,
  Im not clear what is the objective of the lecture? I understand it is an
intro, but what are you trying to achieve?

I didnt read all the details, but maybe you can look into creating a
docker/virtual box image with everything preinstalled.
Good luck.

On Wed, Nov 20, 2019, 11:54 Göktuğ Kayaalp <self at gkayaalp.com> wrote:

> Hi all,
>
> I am responsible of giving my colleagues in from linguistics MA
> programme an intro to Python, and programming, with a focus on
> statistics.  It’ll be a single lecture, and I probably won’t be able to
> do more than give some demos and then some pointers to actually properly
> learn how to use the tools.
>
> The problem is I’m a rather techie power user and my audience the exact
> opposite, so I feel like I could make use of some guidance as to how to
> bridge the gap and be useful.
>
> I want to stick to Python 3, demo them a few basics of programming, then
> how to use matplotlib, Jupyter notebooks (is this what IPyNBs became?),
> and some descriptive statistics.  All this needs to happen within the
> span of a single lecture (tho if people are interested I’ll offer to do
> a few more in our own time), so 45min~1h.
>
> The first problem is installation: apart from me, a Debian user,
> everybody has Windows or Mac laptops, and IDK how you install Python on
> them.  I feel like choosing one of the distros is a good idea: I could
> just put the installers on a USB and hand it out, or just send them a
> message with simple steps to follow and set themselves up beforehand.
> Thing is, IDK nothing about distros.  Anaconda seems to be the best
> options, but comes with complications like an IDE, as opposed to just
> working with notebooks, and is huge.  Also, seems to include R stuff.
> Spyder looks nice, but I don’t want to freak people out with such an
> unfamiliar environment as an IDE just within the first few moments they
> encounter programming.  These are all humanities people.  Another
> problem is that Anaconda has ‘conda’, a non-standard package manager,
> and I’m kinda vary of introducing that to people: should I talk of pip,
> should I leave it out?  I feel like I should just stick to pip and leave
> conda out, but IDK.  Python(x,y) is interesting, but it’s apparently
> Py2k only, and that’s a no-no.
>
> So, am I better off telling people to install Anaconda, or plain Py3k +
> a selection of packages (which maybe I make into a .zip or something)?
>
> Then, I need good pointers to hand out: links to good introductions to
> Python, programming, and statistical use of Python.  Thing is, I’ve
> always learned the hacker way, i.e. skip the docs, tinker with stuff.
> Thus, IDK of any good resources out of experience, and I want to ask you
> all for some recommendations.  I prefer free and tutorial-like stuff,
> but I’ll teach them how to use the stdlib reference too.
>
> What are some good self-teaching material for those who are new to
> programming and Python, and need to mainly do statistics with
> experimental data?
>
> Finally, I’m looking for recommendations on what to show and how.  My
> current master plan is
>
> - what’s the use of programming for a linguist
> - an abstract idea of what programming is
> - basic intro to Python syntax
> - demo how to load and clean up some data
> - demo matplotlib
> - demo jupyter notebooks
> - compare with alternatives: R, SPSS, other?
> - briefly refer to libraries for
>   - NLP
>   - AI?
> - lots of links on
>   - how to learn enough coding for number crunching and plotmaking
>   - how to make use of stdlib reference
>   - how to find and utilise packages and their docs
>   - ...?
>
> I plan to produce a handout with all this info neatly organised, and
> just go with a (few) Jupyter notebooks for the rest (resisting hard the
> urge to go in with Emacs Org Mode instead :)).
>
> I’m looking forward to any recommendations from youse.  The deadline is
> about a month and a half away, and I really want to give people
> something operationable.  People are stuck with BS like SPSS, too simple
> and too pricy, when a few lines of Python (or R) is all they need.  I
> came here because IDK teaching about this stuff, and I haven’t left the
> comfort zones of a programmer ever before, so this is some new
> experience for me and I don’t want to botch it.
>
> Thanks a lot in advance,
>
>        Göktuğ.
>
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> İ. Göktuğ Kayaalp       <https://www.gkayaalp.com/>
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