Talk Teaching Scientific computing in Developing countries

Presented by Victor Miclovich Kisitu in Scientific track 2010 on 2010/07/11 from 15:45 to 16:00 in room Dussane
Abstract

The use of Python and adoption as a tool in scientific computing in least developed countries (LDC) is relatively slow. I want to suggest how we can promote the use of Scipy in LDCs. I have studied science in Africa most of my life and had a few mentors in the US that have guided me in my studies; the Internet has also been revolutionary in my development. That is how I came to know about Python in the first place. It is not popular in faculties across Africa but this doesn't mean it is not used in some courses across Africa. I base my findings on physical interviews with other students, faculty and engineers/scientists I meet.

I am a member of MIT's EPROM faculty and for past few months I've been teaching a small number of engineering students at Makerere university (Uganda) mobile computing. Mobile computing is a pervasive topic and in my classes I always integrate other mainstream branches in science such as Machine learning, Natural language processing and Health to develop applications. This kind of research has created interest among faculty and students and they are slowly growing to like Python even more. My research interests are heavily dependent on the best features that scientific computing has to offer in Python.

The goal of education in the developing has been to "maintain" things engineered and produced by more developed parts of the world. For this to change, scientists from better and conducive scientific environments can be a part of this by reaching out to faculties in LDCs. Now, there are many ways of doing that. Email, telephone, barcamps, conferences, talks, social networks, and others I might not even know exist. That's how we can get to reach out to scientist that will find Scipy, numpy, biopython and range of other Python libraries very useful.