First of all, I am glad to be here and to have the opportunity of sharing my ideas on this collective blog on Operations Research, which is a project that I should especially express my appreciation for. My friends, Sertalp, Ahmet and Pelin are doing a great job by running this blog and I believe that, in the next few years, many people in the field will be following this blog, if we can manage to keep it active.
In my first post, I would like to touch a topic that is closely related to what we are doing here in this blog: Sharing ideas and the knowledge. I would like to talk about open courses on Operations Research.
As a PhD student, in order to internalize a subject in mathematics or in any other field, it is not enough to take its course most of the time. While taking a course for the first time, you may miss some important details. That is why I would go and listen some basic courses again and again in order to completely absorb its intuition, if I had enough time. And there are courses that I took years ago that I did not really use and therefore forgot them. Moreover, I don’t have reach to some courses in my school or I would prefer to listen it from its pioneers at MIT. One can put forward many similar arguments for why most of us need open courses available on YouTube etc. But beyond all of these arguments, in this century, it is senseless to make the (well organized) basic knowledge to privilege to some people, e.g. those who live in the U.S., go to X university, are able to pay more than $1000 to a few text books etc. I think that this is an obstacle in front of the development, in a global and broad sense. For all these reasons, I am a deep-heart fan of open course initiatives.
I cannot tell how much I like being able to listen to Linear Algebra from Prof. Gilbert Strang from MIT, or the Sociology 1 course from Prof. Ann Swidler from Stanford, and similarly, how much I wish to had Operations Research courses online, such as, Dynamic Programming from Prof. Dimitri Bertsekas. Here, in this collective blog on OR, I would like to kindly ask the professors in the universities who are teaching OR courses: If you are teaching an OR course, and if you believe that you are good at teaching, please encourage your university to put them online. It is going to motivate many people, all around the world, to learn this material and employ them in their research in very different fields. Being have to read that material from the book is discouraging for many people, not necessarily because people are lazy, but because learning is affected by many factors, even by the mimics of the professor while explaining the topic.
Here, I want to list some open courses of which the complete set of video lectures are available online at selected universities. If you guys know similar other courses that are not listed here, you can write them down in the comments with a link, so we can use this post as a resource for OR students.
Thanks in advance and see you in the new posts.
* We keep updating the list. Thanks everyone for contributing in the list. Last Update: 02/15/13
Courses on Operations Research (or related):
- Introduction to Algorithms – MIT – Prof. Charles Leiserson
- Linear Programming – Bilkent U. – Prof. Barbaros Tansel
- Analytical Models for Supply Chain – Bilkent U. – Prof. Nesim Erkip
- Facility Location on Networks – Bilkent U. – Prof. Barbaros Tansel
- Stochastic Models – Bilkent U. -Prof. Savaş Dayanık
- Intro. to Modeling and Optimization – Bilkent U. – Prof. Emre Alper Yıldırım
- A Process Outlook for Industrial Engineering – Bilkent U. – Prof. Nesim Erkip
- Intro. to Lean Six Sigma Methods – MIT – Prof. Earll Murman
- Mathematical Methods for Engineers – MIT – Prof. Gilbert Strang
- Machine Learning – Stanford – Andrew Ng
- Design and Analysis of Algorithms – Stanford – Prof. Tim Roughgarden
- Unsupervised Feature Learning – Stanford – Andrew Ng
- Machine Learning – Caltech – Prof.Yaser Abu-Mostafa
- Convex Optimization I – Stanford – Prof. Stephen Boyd
- Convex Optimization II – Stanford – Prof. Stephen Boyd
Courses for necessary Mathematical Background:
- Discrete Stochastic Processes – MIT – Prof. Robert Gallager
- Probabilistic Systems Analysis and Applied Probability – MIT – Prof. John Tsitliklis
- Linear Algebra – MIT – Prof. Gilbert Strang
- Single Variable Calculus – MIT – Prof. David Jerison
- Multivariable Calculus – MIT – Prof. Denis Auroux
- Differential Equations – MIT – Prof. Arthur Mattuck
- Real Analysis – Bilkent U. – Prof. Alexandre Gontcharov
- Discrete Math and Prob. Theory – U.C. Berkeley – Prof. Umesh Vazirani
Online Books on Operations Research:
- Convex Optimization – S. Boyd, L. Vandenberghe – Cambridge University Press