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
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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