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Numerical Methods in Computing Course

Numerical Methods in Computing Course
4 to 360 hours of flexible workload
certificate valid in your country

What Will I Learn?

Gain mastery over essential numerical methods for creating reliable and efficient computations. Cover floating-point basics, error analysis, root-finding techniques, ODE solvers, and quadrature methods. Apply these skills to develop, validate, and optimise a comprehensive numerical library featuring intuitive APIs, automated tests, and high-performance code in contemporary programming languages.

Elevify Advantages

Develop Skills

  • Design stable numerical algorithms by managing floating-point and rounding errors effectively.
  • Implement reliable root-finding solvers including bisection, Newton, secant, and hybrid methods.
  • Solve ODEs numerically using Euler and Runge-Kutta time-stepping implementations with testing.
  • Apply efficient quadrature techniques such as Simpson, trapezoidal, Gaussian, and adaptive rules.
  • Develop robust numerical libraries with clean APIs, unit tests, and performance optimisations.

Suggested Summary

Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.
Workload: between 4 and 360 hours

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