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Numerical Methods in Computing Course

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

What will I learn?

Master the core numerical methods you need to build reliable, high-performance computations in this focused course. Learn floating-point fundamentals, error analysis, root-finding, ODE solvers, and quadrature techniques, then apply them to design, test, and optimize a robust numerical library with clean APIs, automated validation, and performance-aware implementations in modern programming languages.

Elevify advantages

Develop skills

  • Design stable numerical algorithms: control floating-point and rounding errors fast.
  • Implement robust root-finding solvers: bisection, Newton, secant, and hybrids.
  • Solve ODEs numerically: build and test Euler and Runge–Kutta time-stepping codes.
  • Apply efficient quadrature: Simpson, trapezoidal, Gaussian, and adaptive rules.
  • Build tested numerical libraries: 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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