Algebre 3

ECOLE Sup Informatique - IA et Mathématiques ( intelligence artificielle)L2 · DEUXIEME ANNÉE L2

5 chapitres · 5 séances · 6 PDF · 11 vidéos · 1 quiz

Description à venir.

Accéder à ce module Cours vidéo, TD, PDF et quiz — accès après inscription.

Au programme

  1. polynomial rings and groups (st ing, st, math,info ,ing info

    Par Mr Aissaoui Mohammed

    This chapter discusses polynomials in a ring and uses the properties of Euclidean division. The remainder ......

    • groups and rings and construction of polynom rings and groups (st ing, st, math,info ,ing info
      • PDFrings and groups (st ing, st, math,info ,ing info
      • Vidéogroups and rings
      • Vidéopolynomial ring (construction )
      • Vidéoalgebric structures
      • Vidéointegral dmain and polynomial function
      • Quizla structure d'un polynome ( sous forme de question de cours )
    • arethmetic on polynomials on k[x]
      • PDFpGCD (gcd) This chapter reviews the concepts of Algebra 2
      • PDFthe course materials
      • Vidéoroots and euclidean division
  2. Eigen elements : eigenvalues and eigenvectors

    Par Mr Aissaoui Mohammed

    Eigenvalues and eigenvectors are fundamental concepts in linear algebra, providing a powerful way to understand the structure and behavior of linear transformations and matrices. Rather than describing how a transformation changes every vector, eigenvectors identify the special directions that remain unchanged in direction, while eigenvalues measure the corresponding scaling factors.

    • eigenvalues and eigenvectors
      • PDFeigenvalues and eigenvectors
      • Vidéopart 1
      • Vidéopart 2
      • Vidéopart 3
    • TD1
      • PDFTD1 partie 1 .
      • Vidéotd1
      • Vidéotd part 2
  3. Eigen elements, eigenspaces, and the characteristic polynomial

    Par Mr Aissaoui Mohammed

    Eigenvalues, eigenspaces, and eigenvectors reveal the fundamental structure of linear transformations. They describe the directions that remain invariant under a transformation and the factors by which they are scaled. The characteristic polynomial provides a powerful algebraic tool for finding eigenvalues and connects the algebraic and geometric aspects of a matrix.

    • cours
      • Vidéocours
      • PDFcours
  4. Diagonalization of square matrices

    Par Mr Aissaoui Mohammed

    Diagonalization is a fundamental technique in linear algebra that allows a square matrix to be represented in a simpler form using its eigenvalues and eigenvectors. This transformation reveals the internal structure of a matrix and makes many calculations, such as computing powers of matrices, significantly easier.

  5. Triangularization of Square Matrices

    Par Mr Aissaoui Mohammed

    Triangularization is a fundamental technique in linear algebra that allows a square matrix to be transformed, through a change of basis, into an upper triangular matrix. This form preserves the eigenvalues on the diagonal and reveals important structural properties of the matrix.

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