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Valorization Training Human resources and mobility. The main objective of the course is to develop the basic understanding of linear algebra matrices and determinants and Numerical Analisys algorithms to solve mathematical problems on the computer. The student must be able to apply the methods and algorithms to solve problems related to their area of expertise. Vectors and Matrices Definition, operations, rank of a matrix, linear equations systems involving matrices, resolution and coj of these systems, inverse matrix.
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Determinants Definition, properties, calculation of determinants, Cramer’s rule, determination of inverse matrix with determinants. Preliminaries on computing Elementary concepts, errors and convergence.
Solution of nonlinear equations Methods: Bisection, Newton-Raphson and fixed-point. Analysis of the errors. Numerical linear algebra Iterative methods for linear systems and nonlinear systems.
Interpolation and polynomial approximation Lagrange polynomials and divided differences. Integration and numerical differentiation Methods: Problems for initial value ODEs Methods: Planned learning activities and teaching methods Both zplicacoes and practical classes with exposure of the program contents and presentation of examples.
Resolution of proposed exercises in working groups or individually, with guidance from the teacher. Tutorial support is available in English.
Algebra Linear com Aplicacoes Howard Anton, Chris Rorres | Matheus Menezes –
Objectives and Learning outcomes of the Course Unit. This course is an introduction to Linear Algebra and Numerical analysis. Euler, Runge-Kutta and Taylor.
Recommended or required reading. Planned learning activities and teaching methods.
Both theoretical and practical classes with exposure of the program contents and presentation of examples.