Numerical Methods Training Course
Duration14 hours (usually 2 days including breaks)
Knowledge of at least one programming language from R, Python, Octave, and some C++ options.
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
Bookings, Prices and Enquiries
- Public Classroom
- Participants from multiple organisations. Topics usually cannot be customised
- Private Classroom
- Participants are from one organisation only. No external participants are allowed. Usually customised to a specific group, course topics are agreed between the client and the trainer.
- Private Remote
- The instructor and the participants are in two different physical locations and communicate via the Internet. More Information
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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