TA Lab · Autumn 2022

Numerical Methods Lab

Independent University, Bangladesh

Autumn 2022 Independent University, Bangladesh 28 students Course repository

Summary

Lab worksheets and assignments for numerical methods — root-finding, interpolation, numerical integration, and ODEs — implemented in Python.

Learning outcome
Students can implement and analyze core numerical methods, understand their error characteristics, and apply them to scientific computing problems.

Weekly schedule

  1. Lab 01–02 Floating point arithmetic and error analysis
  2. Lab 03–04 Root-finding: bisection, Newton-Raphson
  3. Lab 05–06 Polynomial interpolation and splines
  4. Lab 07–08 Numerical differentiation and integration
  5. Lab 09–10 Linear systems: Gaussian elimination and LU factorization
  6. Lab 11–12 Ordinary differential equations: Euler and Runge-Kutta

Tutorial content

#01 Floating point and machine epsilon coming soon
#02 Root-finding methods coming soon
#03 Lagrange and Newton interpolation coming soon
#04 Numerical integration: trapezoidal and Simpson's rule coming soon
#05 Solving linear systems coming soon
#06 ODE solvers: Euler and RK4 coming soon

Resources & references

  • Numerical Methods for Engineers — Chapra & Canale open
  • SciPy documentation open
  • Course GitHub repository open