Ph.D. in Applied Mathematics (Statistics)
Ph.D. in Applied Mathematics (Statistics)


INSA Rouen Normandy 2019-2021​

  • Introduction to machine learning with Gilles Gasso:
  • Statistics with Bruno Portier:
    • Times series,
    • Linear regression (simple and multiple)
    • ANOVA1 and ANOVA2
  • Inferential statistics with Bruno Portier:
    • Point estimation
    • Interval of confidence
    • Hypothesis testing
  • Matrix computation Gilles Gasso and Benoit Gaüzère
    • Matrix Factorizations : LU, LDL and Cholesky factorization, QR factorization
    • Solving  linear system
    • Review of Least squares problem
    • Application of matrix factorizations
    • Iterative methods (Jacobi, Gauss-Seidel, relaxation)
    • Algorithms for Eigenvalues and Singular values computation
  • Introduction to inferential statistics with Alexandrina Rogozan: Practical work with Python on inferential statistics (TP1, TP2, TP3, TP4, TP5, TP6 )
  • Updating in Maths with Benoit Gaüzère: Linear algebra, real analysis and complex numbers.

Université virtuel du Senegal Feb. 2021 (UVS):

Project in machine learning with Pyhton (24Hours): It consist on the implementation of the following approach : Multipe linaire regression, Ridge, variable selection, Lasso, Elastic-net. The objectif is to use theses methods (with python) in order to predict the price of an appartement. [TP] [data set]