Numerical Methods Training Course

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Course Language

This course is delivered in German or English.

Course Code

67795

Duration Duration

14 hours (usually 2 days including breaks)

Requirements Requirements

Knowledge of at least one programming language from R, Python, Octave, and some C++ options.

Overview Overview

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.

Course Outline Course Outline

Topics Covered:

  • curve fitting
  • regression robust regression
  • linear algebra: matrix operations
  • eigenvalue/eigenvectormatrix decompositions
  • ordinary & partial differential equations
  • fourier analysis
  • interpolation & splines

Public Classroom Public Classroom
Participants from multiple organisations. Topics usually cannot be customised
From 2250EUR
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Private Classroom 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.
From 2250EUR
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Private Remote Private Remote
The instructor and the participants are in two different physical locations and communicate via the Internet
From 1750EUR
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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.

Number of Delegates Public Classroom Private Classroom Private Remote
1 2250EUR 2250EUR 1750EUR
2 1450EUR 1425EUR 1175EUR
3 1183EUR 1150EUR 983EUR
4 1050EUR 1013EUR 888EUR
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