Numerical Methods With Python MOOC Starts Today
Monday, 18 August 2014

An interesting sounding MOOC that will help students implement numerical solution methods in well-designed Python programs starts on August 18.

The course was announced at last months SciPy (Scientific Python) conference where Professor Lorena A Barba, who will be one of four instructors for the MOOC, MAE6286: Practical Numerical Methods with Python, delivered using Open edX software.

The MOOC is taking place in conjunction with four on-campus credit bearing classes for first-year graduate students at  

George Washington University (Washington, DC, USA)

King-Abdullah University of Science and Technology (Saudi Arabia)

University of Southampton (UK)

Pontifical Catholic University of Chile (Santiago, Chile)

It is described as:

a groundbreaking example of inter-institutional (across four continents!) collaboration in open education. Although the MOOC will be run from GW, all four instructors will be collaborating openly in the development and design of course content and learning objects, and all materials will be released under open licensing models (content under Creative Commons Attribution CC-BY 4.0 and code under MIT license).

The decision not to go with Coursera, edX or any similar MOOC providers is a deliberate one, in keeping with its ideals of open education:

The associated MOOC will be independent of any of the well-known providers: we will deploy our own instance of the Open edX software on cloud hosting services to offer a MOOC without surrendering our IP to for-profits nor subjecting students to creepy data mining. We believe that higher education is the core mission of universities and we want to contribute to open education with for-profit companies having only a supporting role.

This also means that all course materials will be freely available; videos will be on YouTube and can be viewed without being registered in the course and lessons will be on GitHub and can be downloaded by anyone.


For students who want to register and earn badges for participation, the course runs from August 18 to December 6 and has an estimated workload of around 6 hours per week.

By way of prerequisites you need a background in vector calculus, linear algebra, and differential equations. You will also need Python since the leaning modules will be provided as IPython Notebooks, and for this there are two options. You can install a full Python distribution (either 2.7 or 3.4) such as  Anaconda or Canopy. Option two is to use a web-based Python system, like a free Wakari account or Pythonanywhere.

Over the course of the MOOC, students will learn to: 

  • connect the physics represented by a mathematical model to the characteristics of numerical methods to be able to select a good solution method;
  • implement a numerical solution method in a well-designed, correct computer program;
  • interpret the numerical solutions that were obtained in regards to their accuracy and suitability for applications.


The title of the first module is "The phugoid model of glider flight" and the next one is "Space and Time—Introduction to finite-difference solutions of PDEs". More details of these and the subsequent three modules are already on the course website and the team is still working on the final two.

This MOOC is likely to appeal to students for its approach as well as its content. To quote from its "Who is the course for": 

In developing this course, the instructors are inspired by the philosophy of open-source software. One of the tenets of the course is that we can use the web to interact, connect our learning, teach each other by sharing our learning objects. Therefore, this course is especially for those who are eager to participate in distributed knowledge creation on the web. Join us in this adventure!

The biggest problem for any MOOC that, for perhaps good reasons, doesn't go with the big providers has to solve is getting students. The big MOOC providers have an audience of existing students that new courses are advertised to when they are announced. Independent MOOCs need publicity to put the "Massive" in MOOC. So do spread the word about this one.

If you know of a CS related course that is about to start email me. 


More Information

MAE6286: Practical Numerical Methods with Python

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Last Updated ( Monday, 18 August 2014 )