Numerical Methods in Computing Course
This course teaches numerical methods essential for computing, enabling students to create faster and more reliable technology solutions. Key topics include root-finding techniques, ODE solvers, numerical integration, error control, and designing robust algorithms for high-performance software and data-intensive applications. Participants will gain practical skills to implement and optimise these methods effectively.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain mastery over essential numerical methods for reliable high-performance computing. The course covers floating-point basics, error analysis, root-finding algorithms, ODE solvers, and quadrature methods. Students will apply this knowledge to develop, test, and refine a comprehensive numerical library featuring intuitive APIs, thorough automated testing, and optimised implementations using 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 such as Simpson, trapezoidal, Gaussian, and adaptive rules.
- Build tested numerical libraries with clean APIs, unit tests, and performance tuning.
Suggested summary
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