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.g

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 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 http://www.astroml.org This is a padova isochrone query tool for python: https://github.com/jonathansick/padova https://github.com/jonathansick/padova MCMC library, arguably better than pymc, written by astronomers: https://github.com/dfm/emcee https://github.com/dfm/emcee Lifesaver on how to make fancy plots: http://matplotlib.org/gallery.html http://matplotlib.org/gallery.html Not python specific, tools of the trade: http://aladin.u-strasbg.fr http://aladin.u-strasbg.fr (star chart with survey data overlays), http://www.star.bris.ac.uk/~mbt/topcat/ 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 http://ds9.si.edu/site/Home.html (CCD image visualization), http://iraf.noao.edu 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 http://astrobites.com