The course aims to introduce the student to the numerical problems that can face us when building numerical algorithms to solve some mathematics problems numerically, and also to introduce the student to the basic numerical methods and how to use them to find approximate numerical solutions to some of these problems that are difficult to solve by algebraic or analytical methods. It enables the student specifically to: explain the use of numerical methods in solving various scientific problems when it is difficult or impossible to solve them by analytical methods, and use numerical methods to find approximate solutions to the problems posed With the use of computers such as derivation and integration, also the application of numerical integration to calculate non-computable integrals through original functions, matrix analysis and the habit of using large-dimensional matrices, training in exercises in lecture, at home and in office hours, searching the Internet, and finally simplifying ways to find the solution of equations that need more than one method clearly and accurately.
Intended learning outcomes
At the end of the course, the student must: to identify and analyze the most important numerical methods used to solve algebraic and non-algebraic equations such as the method of halving fields, the method of secant and the method of Newton, and analyzes and masters the use of the most famous numerical methods in calculating specific integrals and estimating the errors committed, such as the method of rectangles, the method of trapezoidal and the method of Simpson, and also identify the most important direct and iterative methods used in solving sentences of linear equations. In addition to the least squares method and the reverse completion process, Lagring recognizes, analyzes and masters the use and study of the convergence of the most important recursive methods used in solving sentences of linear equations such as Jacobi's method and Gausss-Seidel's method.