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Numerical Methods in Computing Course

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

What will I learn?

Master essential numerical methods for reliable, high-performance computing. Delve into floating-point basics, error analysis, root-finding algorithms, ODE solvers, and quadrature methods. Apply these skills to design, test, and optimise a robust numerical library featuring clean APIs, automated validation, and efficient implementations in contemporary programming languages.

Elevify advantages

Develop skills

  • Design stable numerical algorithms by controlling floating-point and rounding errors effectively.
  • Implement robust root-finding solvers including bisection, Newton, secant, and hybrid methods.
  • Solve ODEs numerically by building and testing Euler and Runge-Kutta time-stepping codes.
  • Apply efficient quadrature techniques like Simpson, trapezoidal, Gaussian, and adaptive rules.
  • Build tested numerical libraries with clean APIs, unit tests, and performance tuning.

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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