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Scientific computing with python - Coggle Diagram
Scientific computing with python
CH1: Introduction to programming with Python
Basic operations of Python programming
Introduction and installation of the Jupyter environment
CH2: Numerical solution of systems of linear equations
Implementing of iterative method for solving systems of linear equations
Application of programmed methods to solve a real problem.
Implementing direct methods for solving systems of linear equations.
CH3: Polynomial interpolation
Comparison of the two methods in terms of computing time.
Real application
Polynomial interpolation by Lagrange and Newton's method.
CH4: polynomial approximation
Fitting data by a non-linear polynomial model
Fit data by a linear polynomial model
Real application
CH5: Numerical integration using python
Real application
Implement numerical integration and derivation methods
CH7: Numerical solution of ordinary differential equations
Implement the explicit Euler and implicit Euler
Real application
Compare the two methods in terms of computation time and accuracy.
CH6: Numerical solution of nonlinear equations
Compare the two methods in terms of computation time and accuracy.
Real application
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Implement the method of Dichotomy and Newton