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
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.What our students say
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