Numerical Methods in Computing Course
This course teaches numerical methods for computing to create reliable software. Students learn root-finding techniques, ODE solvers, numerical integration, error analysis, and algorithm design. They apply these skills to develop high-performance numerical libraries with testing and optimization 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 dependable computations. Cover floating-point basics, error control, root-finding algorithms, ODE solvers, and integration techniques. Use them to create, validate, and refine a numerical library featuring intuitive interfaces, automated tests, and efficient code in current 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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