Numerical Methods in Computing Course
This course equips you with essential numerical methods for computing to create faster, more reliable technology solutions. You will master root-finding techniques, ODE solvers, numerical integration, error control, and robust algorithm design, enabling you to develop high-performance software and data-intensive applications with confidence and precision.

from 4 to 360h flexible workload
certificate valid in your country
What will I learn?
Gain mastery over key 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 comprehensive 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.What our students say
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