HI Owen, My wife and I (she teaches Renaissance English and is definitely a Humanities person) are "taking" the course together. My Google+ comments are here <http://goo.gl/aGjeV> and here<https://plus.google.com/u/0/114865618166480775623/posts/WBmyR69MsCF>. I'm not certain what the structure of the course is. The lectures all seem to be uploaded, but I haven't seen anything about a timeline, exercises, tests, or any other structure for the course. Do you know anything about that?
*-- Russ Abbott* *_____________________________________________* *** Professor, Computer Science* * California State University, Los Angeles* * Google voice: 747-*999-5105 Google+: https://plus.google.com/114865618166480775623/ * vita: *http://sites.google.com/site/russabbott/ *_____________________________________________* On Tue, Feb 28, 2012 at 9:14 AM, Owen Densmore <[email protected]> wrote: > The Stanford Modeling Class has started, I thought I'd give a summary of > what's up so far. The website is: https://www.coursera.org/modelthinking/ > > First of all, this is NOT a deep dive into exotic techniques. Rather it > is a *very* broad overview of modeling, answering the question "why model". > With each discussion point Scott gives concrete examples, but without > having to write code or "do the math". > > The name of the class, Model Thinking, captures this difference: he is > guiding us through a new way of thinking that is precise and relatively > well understood by now. > > So it is much more a very high level view of modeling (mainly Agent Based > Modeling but also simple mathematical and graphical models) with the > emphasis on very clear thinking. > > One quick example: Aggregation. This is the reductionist dilemma. How do > you either > > 1 - Look at a Macro event and deduce its parts, or > 2 - Look at simple Micro rules and deduce the results. > > Water, a micro molecule and a macro substance. The molecule cannot be > "wet". Or Schelling's segregation model: at the micro level, individuals > are quite tolerant, wanting only a few like neighbors, yet the result is a > surprising large value of segregation. He also introduces a metric for > segregation, The Dissimilarity Index, so we can be precise. He also looks > at the Game of Life and CA's in a similar way. > > Unlike the Machine Learning class, there are readings, generally classics > in the field. The first session's readings, for example, are Josh > Epstein's "Why Model" and Scott's introduction to his class. Both are very > "humanities" over "computation". > > I've uploaded my class notes, 2 2/3 sets thus far: they are screen > captures with pdf annotations. You can get a feel for the class quickly by > thumbing through them. They are at http://backspaces.net/temp/ and begin > with ModelThinking. > > I do have to confess: there is a method in my madness in writing this > email. I find learning in a cave, by myself, less fun than having some > others along for the ride. So if anyone does take the bait .. and ends up > following the class, lets get together and chat about it. And don't feel > you have to be a Scientist or Mathematician or Hacker .. you don't. > > -- Owen > > ============================================================ > FRIAM Applied Complexity Group listserv > Meets Fridays 9a-11:30 at cafe at St. John's College > lectures, archives, unsubscribe, maps at http://www.friam.org >
============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
