Nothing really productive to say to anyone except professional astronomers in the room:

This is a similar tutorial we went through at ESA: http://python4esac.github.io/index.html

This is a more advanced machine learning focused module, go through the "book figures" and example code is given. I also have a collection of slides on the module if anyone is interested: http://www.astroml.org

This is a padova isochrone query tool for python: https://github.com/jonathansick/padova

MCMC library, arguably better than pymc, written by astronomers: https://github.com/dfm/emcee

Lifesaver on how to make fancy plots: http://matplotlib.org/gallery.html

Not python specific, tools of the trade: http://aladin.u-strasbg.fr (star chart with survey data overlays), http://www.star.bris.ac.uk/~mbt/topcat/ (table manipulation and quick visualization for CSV, FITS, VOTable, IPAC, etc.), http://ds9.si.edu/site/Home.html (CCD image visualization), http://iraf.noao.edu (a house of cards build by grad students for grad students where no one really knows how it works but everyone seems to know about)

Please cite these resources if you use them.

Finally, a fun link for grad students: http://astrobites.com