Lecture I:
Introduction: distance matrices, scattered data interpolation, basic MATLAB routines, approximation in high dimensions and using different designs

Lecture II:
RBF interpolation and MLS approximation: approximate approximation and the connection between the two methods via residual iteration

Lecture III:
Dealing with Ill-Conditioned RBF Systems: various preconditioning and regularization ideas

Lecture IV:
``Optimal" shape parameters for RBF approximation methods

Lecture V:
RBF collocation and polynomial pseudospectral methods

Lecture VI:
Nonlinear Problems: Nash iteration and implicit smoothing