Numerical Methods in Computing Course
This course teaches numerical methods for computing, focusing on building reliable and high-performance software. Students learn floating-point basics, error analysis, root-finding techniques, ODE solvers, and quadrature methods. They apply these to design, test, and optimise numerical libraries using modern languages, ensuring clean APIs, automated validation, and efficient implementations for data-intensive applications.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain expertise in essential numerical methods for reliable computing. Cover floating-point arithmetic, error control, root-finding algorithms, ODE solvers, and integration techniques. Build and validate a complete numerical library with robust APIs and performance optimisations in contemporary programming languages.
Elevify advantages
Develop skills
- Design stable numerical algorithms by controlling floating-point and rounding errors.
- Implement robust root-finding solvers including bisection, Newton, secant, and hybrid methods.
- Solve ODEs numerically using Euler and Runge-Kutta time-stepping techniques.
- Apply efficient quadrature methods 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 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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