I have not studied this in detail, but it seems like this resource could have been presented as a series of IPython Notebooks. IPyNb with its literate programming emphasis is a wonderful pedagogical tool allowing users to interactively experiment with code.
As a non-neuroscientist, the WashU course on Coursera about Computational Neuroscience was also really good. Not sure if there's an upcoming offering, but I'd highly recommend taking it. Keep in mind it's heavy on computation on a "simulate neurons and small networks of neurons" level and light on top-down neuroscience
Related, a few years ago I wrote a series of blog posts with code and discussion on how to do some basic neural simulations in Python: http://www.neurdon.com/author/byron/. This includes spiking leaky integrate-and-fire neurons, the Hodgkin-Huxley neuron model, and the Izhikevich model neurons.
Cool! I'm currently doing summer research modelling neurons and your posts really helped me learn this stuff. I would go through your code line-by-line writing it out and then I'd just play with the parameters. It was a nice starting point. Thanks!
https://github.com/mef51/HodgkinHuxleyNeurons
