Question: would people be interested in summarized transcripts for these lectures?<p>The reason I ask is because I know I'm not going to watch 20 hours of the videos, and when I take a look at the transcripts they are good, but they are also long. It would take a while to even skim them.<p>I've been doing some work around machine text summarization, and it seems like these transcripts would be a great candidate to put it to work.<p>What do people think? Would you like summaries of the transcripts of these lectures?<p>EDIT: Thanks for the positive feedback, I'll submit them as a story here in 24 hours (right now I'm supposed to be getting ready for a big dinner tonight).
OpenCourseWare is great but I sort of feel like it's been so hyped over the years. Think about how long its been around, now look at how few courses have videos or any content worth mentioning at all. I could understand some of the other disciplines lagging behind in content but really it's the computer science stuff that is quite sparse. They have a big list but most of the courses just have some assignments without solutions or some lecture notes, which are available from most university web sites anyway.
I'm going to take this opportunity to plug my OpenCourseWare app for boxee. You can enjoy a lot of what OpenCourseWare has to offer (including this course) from the comfort of your couch (Currently the app has courses from MIT, Yale, Stanford, Berkeley and UCLA).
You can get a lot of CS lecture series on Academic Earth including MIT's Intro to Algorithms:<p><a href="http://www.academicearth.org/subjects/computer-science" rel="nofollow">http://www.academicearth.org/subjects/computer-science</a><p>There are other disciplines there too:<p><a href="http://www.academicearth.org/subjects/" rel="nofollow">http://www.academicearth.org/subjects/</a>
You can't replace CLRS as a reference, but I recommend the following free draft if you're looking for an algorithms text to start out with: <a href="http://www.cs.berkeley.edu/~vazirani/algorithms.html" rel="nofollow">http://www.cs.berkeley.edu/~vazirani/algorithms.html</a>.
That's a good set of lectures.<p>My girlfriend recently did several as she was learning about CS as a postgrad, and found them very useful.<p>They, and many more, are also available on 'iTunes university' from within the iTunes interface. The Stanford CS courses that are up are also well worth a look; there's a good Machine Learning course up there.<p>The only issue is that the videos often aren't properly edited for the Internet. They don't strip out the class administrative parts, and the lectures would go a lot better with a navigable text index to allow you skip to different parts of the video.
The Khan Academy is also worth a look as a similar project.<p>With a little more care and attention to editing and presenting for the web, this could have a big impact on education.
Not to hijack the thread too much, but are there good resources on learning about algorithm correctness, complexity, recurrence relations, automata and proving techniques? At the moment I'm not doing so well in the proof by induction department, and the course material at UToronto is quite lousy.
I think those lectures can be summarized a lot if the audience has some advanced background. The authors could put some tag in the content, revealing what type of content is about background and core material. Going directly at the core is great when you know well the background material.
IMHO I feel that CLRS is a great book. I consider it to be my bible of algorithms. I have viewed almost all the videos the course ware apart from the last few which constitute of advanced topics. :)