Numerical Computing

Course Purpose
The purpose of this lecture is for students to obtain skills and knowledge of recipes for research related to numerical calculations.
Learning Goals
Students will be able to understand the fundamental procedures of repetition and truncation of numerical calculations, and become familiar with the algorithms of solver, fitting, minimisations, and matrix operators.
Topic
Session 1Python, sympy intro simplified version (programming)
Session 2Explanation of the previous year's exam questions
Session 3Algebraic equations, errors, matrices, interpolation and numerical integration, linear least squares, nonlinear least squares, FFT, differential equations
Session 4Error
Session 5Matrix calculation [1, Introduction to the matrix]
Session 6Matrix calculation [2, Reverse matrix]
Session 7Matrix calculation [3, Eigenvalues and libraries]
Session 8Interpolation and numerical integration
Session 9Linear least squares method
Session 10Non-linear least squares method
Session 11Utilization and principle of fast fourier transform
Session 12Application of differential equations
Session 13Exam rehearsal
Session 14Exam (bring your own laptop)
＊＊This content is based on April 1, 2024. For the latest syllabus information and details, please check the syllabus information inquiry page provided by the university.＊＊