Waiting for the video lectures...
Btw. I am Super Excited to hear this :D
The videos will be recorded this fall semester; Erik will be lecturing again, along with the equally awesome Srini Devadas. In the past, when Erik has recorded his own lectures, I recall that they were posted as soon as they were edited. Every time I've worked with OCW, though, one of their staff members comes in and collects materials at the end of the semester.
I'm not sure exactly what the material differences will be; that's the lecturers' call (way above my pay grade!). If you want more than 6.006 offers, though, check out 6.046, which is the follow-on undergraduate algorithms course.
Since we're doing as much of our planning now as possible, I'm curious: what sorts of things do you wish we'd include? Does anyone have suggestions?
Make every homework a contest on the fastest implementation,e.g. see Tim Bray's Wide Finder benchmark: http://www.tbray.org/ongoing/When/200x/2007/10/30/WF-Results
Python is great for teaching, but I'd let them do the optimizations in any language.
Use problems from your current research as examples/assignments, rather than boring textbook problems.
Let them work with real data: http://www.quora.com/Programming-Challenges-1/What-are-some-... , http://www.quora.com/Data/Where-can-I-get-large-datasets-ope...
Add parallel algorithms to the mix. Ask to parallelize serial algorithms that you explain in the lecture. They should at least start thinking about programming for multicore and clusters, they will thank you for that later.
* Try Adding some more lesser known but useful data structures like Trie,Bloom filters etc.
* Covering recent industry topic - explanation of core concepts that drive bigtable,hadoop, nosql etc.
* Mobile programming from algorithmic prospective.