Numerical Methods in Computing Course
Gain mastery in numerical methods for computing to create faster and more reliable technology solutions. This course covers root-finding techniques, ODE solvers, numerical integration, error management, and designing strong algorithms for high-performance software and data-heavy applications. You will learn to implement these methods using modern programming languages to develop efficient numerical libraries with proper testing and optimisation.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Master essential numerical methods for reliable and high-performance computing. This course teaches floating-point basics, error analysis, root-finding algorithms, ODE solvers, and quadrature methods. You will apply these skills to design, test, and optimise a strong numerical library featuring clean APIs, automated tests, and efficient implementations in current programming languages.
Elevify advantages
Develop skills
- Design stable numerical algorithms by controlling 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 techniques with testing.
- Apply efficient quadrature methods like Simpson, trapezoidal, Gaussian, and adaptive rules.
- Build robust numerical libraries with clean APIs, unit tests, and performance optimisation.
Suggested summary
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