Today there was a workshop at my uni, organized by my Professor Sven Behnke, together with my colleagues Hannes Schulz, Nenard Birešev and me.
The target group was a local graduate school with a general scientific background, but not much CS or machine learning.
The workshop consisted of us explaining the methods and the students then playing around with them and answering some questions using IPython notebooks that we provided (if you still don't know about IPython Notebooks, watch this talk now).
Using the notebooks worked out great! There is only so much you can teach in a 5 hour workshop but I think we got across some basic concepts of machine learning and working with data in Python.
We got some positive feedback and the students really went exploring.
We covered PCA, k-means, linear regression, logistic regression and nearest neighbors, including some real-world examples.
You can find all resources, including tex and notebooks for generating figures etc. on github.
You are welcome to reuse our material, though dropping us a line would be nice.
I haven't asked my coauthors about licensing but I think it shouldn't be a problem as long as you attribute.