Explanations that appeal to intuition have a big effect on learning
The CS229 Machine Learning video lectures are one of the most popular online courses that helped to start the MOOC phenomenon as well as Coursera as a company (Instructor Andrew Ng is Coursera’s co-founder). They are a very good resource to learn about machine learning even for people with already some training in ML.
It’s interesting now to compare the original “CS229″ course from Stanford with the new edition on coursera. While the original videos record full lectures in a classroom with handwriting on chalcboards etc., the new material has newly filmed video chunks per sub-topic, new slides (partly pre-filled, partly hand-edited while Ng explains a topic) and (as it seems to me) prompted text that is in perfect harmony with the slides. As far as I can see, the covered content (with respect to what you learn on ML; some of the math is skipped, though) is broadly identical.
So what’s so interesting? The effect this has on learning! The better presentation of the material (lots of didactics involved) leads to the impression that the level of the course is much lower (somewhere around being suitable for high school students). But in fact its just better conveyed and thus much easyer to understand. Not the covered material is lower level – but good explanations (that appeal to intuition) help a lot!
Disclaimer: this is my impression after having watched only the first few lectures from both courses up to, say, linear regression.