I’ve been teaching a graduate course on graphical models, using the Koller/Friedman book, and based largely on the lecture notes from Carlos Gustrin (formerly at CMU) and Andrew McCallum (UMASS).   I tend to be rather less mathematics-first in my preferred attack on these topics, though, which gives a rather different spin to these lectures.  For example, here’s my version of the (rather long) lecture on random sampling, done as PPT with live, in-class annotation.   Bug me if you’d like to see any of the other lectures.

MOOCs:   Coursera course, VLSI CAD: LOGIC TO LAYOUT

I’m teaching the first VLSI oriented MOOC on Coursera sometime in early 2013 (best guess).  This is a version of my class from Carnegie Mellon, moved into the MOOC era, with all the assignments uploaded and evaluated in the cloud.  Topics include computational Boolean algebra, logic synthesis, technology mapping, timing, placement and routing.  This is high-level tour of the foundational algorithms that make it possible for people to design chips with a zillion elements, taught from a CS sort of angle.  Aimed at folks who want to build tools, and also at people doing real chip designs, who want to know why the tools behave the way they do.


I’ve been fortunate to be part of several interesting curriculum design efforts,  over the last 25 years of my life in academia.  Here a couple of those historical papers.


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