Numerical Methods Training Course
This course is for data scientists and statisticians that have some familiarity with numerical methods and have at least one programming language from R, Python, Octave, and some C++ options. The emphasis of this course is on the practical aspects of data/model preparation, execution, post hoc analysis and visualization.
The purpose of this course is to give a practical introduction in numerical methods to participants interested in applying the methods at work.
Sector specific examples are used to make the training relevant to the audience.
- curve fitting
- regression robust regression
- linear algebra: matrix operations
- eigenvalue/eigenvectormatrix decompositions
- ordinary & partial differential equations
- fourier analysis
- interpolation & splines
The more delegates, the greater the savings per delegate. Table reflects price per delegate and is used for illustration purposes only, actual prices may differ.
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