# Coursera Explodes with courses from 12 Universities..

 6 Here is email I got from coursera today morning Dear Courserians, We are THRILLED to announce that 12 universities -- including three international institutions -- will be joining Princeton University, Stanford University, University of Michigan, and University of Pennsylvania in offering classes on Coursera. On Coursera, you will now be able to access world-class courses from: - California Institute of Technology - Duke University - Ecole Polytechnique Federale de Lausanne - Georgia Institute of Technology - Johns Hopkins University - Princeton University - Rice University - Stanford University - University of California, San Francisco - University of Edinburgh - University of Illinois at Urbana-Champaign - University of Michigan - University of Pennsylvania - University of Toronto - University of Virginia - University of Washington  You'll be able to choose from more than 100 new courses, from learning how to program in Scala (taught from the creator of Scala, Professor Martin Odersky from EPFL), to Professor Dan Ariely's course on irrational behavior, to the legendary UVA course "How Things Work" with Professor Louis Bloomfield. You can check out the most current course list here -- keep in mind you can enroll in a class even if the start date is to be announced. To date, 700,000 students from 190 countries have participated in classes on Coursera, with more than 1.6 million course enrollments total! To everyone who has taken a class on Coursera, or who has recommended us to your friends and family -- thank you! Education is starting to look very different, and we're excited and humbled to be part of it. Very best, Your Coursera Team | www.coursera.org asked 17 Jul '12, 06:11 akrocks 3.2k●11●64

 5 NY Times Article today about Coursera Interesting comment from the article comment section: bgoffe Baldwinsville, NY I wonder how MOOCs use the latest research in how to teach large classes without lecture? In "Improved Learning in a Large-Enrollment Physics Class" Deslauriers, Schelew, and Wieman, Science, May 13, 2011, http://www.cwsei.ubc.ca/SEI_research/index.html , the authors find two standard deviations more learning from non-lecture methods than from lecture from a skilled instructor. Note that Wieman is a Nobel Laureate and a U.S. Professor of the Year (given for teaching). He's currently Deputy Science Adviser to the President for science education. To see such a class in action, here's Eric Mazur of Harvard's physics department: http://www.youtube.com/watch?v=lBYrKPoVFwg . For Mazur's odyssey to not lecturing in class, see "Farewell, Lecture?" Science, January 2, 2009, http://mazur.harvard.edu/publications.php?function=display&rowid=635 . answered 17 Jul '12, 11:50 rseiter ♦ 6.6k●5●25
 2 Martin Odersky on Functional Programming Principles in Scala and Geoffrey Hinton on Neural Networks for Machine Learning, nice to be able to learn straight from the horse's mouth! answered 17 Jul '12, 09:49 Ale 808●10
 1 Though it's TBA, I'd highly recommend Magnus Egerstedt's (GA Tech) mobile robotics course. Best prof I've had in person. Too many classes, so little time... answered 17 Jul '12, 09:05 beard 296●1●10 2 "Too many classes, so little time..." I totally agree with you on this :( (17 Jul '12, 09:33) rbk @beard I overlooked your recommendation in July, but now that the class is live I wanted to call it out. It's a good course and I find Prof. Egerstedt to be engaging and skilled at presenting concepts in formal and informal fashion simultaneously. (04 Mar '13, 10:07) rseiter ♦
 0 I wonder why Coursera is offering redundant courses. They have Algorithm course which is offered by multiple univs/professors and also its introductory programming courses. answered 18 Jul '12, 14:48 rbk 1.2k●1●3●21 2 There is a good explanation of that in the description of Robert Sedgewick's course. His course is meant to be an introduction to algorithms (with applied character), while Roughgarden's course is more theoretical. How does this course differ from Design and Analysis of Algorithms? The two courses are complementary. This one is essentially a programming course that concentrates on developing code; that one is essentially a math course that concentrates on understanding proofs. This course is about learning algorithms in the context of implementing and testing them in practical applications; that one is about learning algorithms in the context of developing mathematical models that help explain why they are efficient. In typical computer science curriculums, a course like this one is taken by first- and second-year students and a course like that one is taken by juniors and seniors. (18 Jul '12, 16:36) fastred I had the feeling that Roughgardens course would be more practical and Sedgewicks courses in algorithms would work up to his two analytic combinatorics courses. (18 Jul '12, 17:01) BayesianHorse @fastred, thanks for that piece of info.. I missed to see it on the FAQs.. so we're getting a choice of whether we want more theory or more practice... @BayesianHorse, I think his analytic combinatronics course would be more of theory and senior/graduate level course while his introduction to algorithms would be a sophomore/junior level course. I have his Algorithms book and the material in it is easier to digest than CLRS! (18 Jul '12, 17:49) rbk 2 Sounds like even if they were to have the same amount of theory/application in their approaches, they'd both be worth doing for those interested in algorithms. I thought Andrew Ng's ML class was incredible, but I'm still finding the CalTech ML one helpful as well. It doesn't stand out as being much more theoretical or anything, but getting different approaches from different professors helps me understand subjects much better, and ML is something that especially interests me. Though I agree it seems unexpected that they would offer redundant courses. But hey, the more, the merrier! (18 Jul '12, 17:58) beard "the more, the merrier!" - I agree with that :) (18 Jul '12, 18:10) rbk I'm currently taking Roughgarden's class and it's pretty heavy on the math. There are programming assignments but no discussion of programming in the lectures/materials. Data sets are provided and students implement algorithms (and variations) and submit the results. If you enjoy mathematical modeling and already are a reasonable coder in a language of your choice then this course is great. (18 Jul '12, 19:25) Norm Deplume ♦
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