Yesterday I visited MCAST since I was one of the judges examining student programming projects. What really struck me is the fact that the majority of projects, although technically sound, didn't really explore any new areas or ideas ... a situation of more of the same. Would have expected much better from young students who were given free hand on the topics or areas to focus on. Although not a teaching expert myself, i think that it is highly important that teachers and the teaching model itself introduce creative thinking methods as part of the IT students curriculum.
In specific software areas like in quantitative finance or else in other mathematical domains, data centric programming typically requires a good balance between three requirements - (1) a solid platform with rich mathematical/statistical functionality (2) having an easy to use, contemporary, programming environment which permits easy and flexible front end code development and (3) an easy to use interface between the two environments. In this artcile I am going to explain how such a balance can be attained by using two of the best products in their specific worlds - using the rich R library as the mathematical/statistical component but then interfacing with C# for the front end application design. As an interfacing option I banked on using R (D)COM which provides an easy to use interfacing method which keeps you away from spending hours identifying interfacing problems. The software required for this tutorial is the following: 1. R software ( download from here ) 2. R (D)COM In...
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