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Numerical Methods in Computing Course

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

What will I learn?

Gain mastery in essential numerical methods for reliable, high-performance computing. Cover floating-point basics, error analysis, root-finding, ODE solvers, and quadrature, then build, test, and optimise a numerical library with clean APIs, automated tests, and efficient implementations.

Elevify advantages

Develop skills

  • Design stable numerical algorithms by controlling floating-point and rounding errors.
  • Implement robust root-finding solvers including bisection, Newton, secant, and hybrid methods.
  • Solve ODEs numerically using Euler and Runge-Kutta time-stepping techniques.
  • Apply efficient quadrature methods 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 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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