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 programming languages with clean APIs and automated validation 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 computations. Cover floating-point arithmetic, error analysis, root-finding algorithms, ODE solvers, and quadrature techniques. Use them to create, test, and optimise a numerical library featuring clean APIs, automated tests, and efficient implementations 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
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