Analyse Numérique (28 hours of teaching)
Undergraduate Course, Polytech, 2026
An introduction to numerical analysis, including Euler’s method.
Teaching
The Variational EM Algorithm (10 hours of teaching)
Graduate Project, Polytech, 2026
The goal was to replicate the results of the following article: Daudin, J. J., Picard, F., & Robin, S. (2008). A mixture model for random graphs. Statistics and computing, 18(2), 173-183.
How many clusters are there in the galaxy dataset? (10 hours of teaching)
Graduate Project, Polytech, 2025
The goal was to replicate the results of the following article: Grün, B., Malsiner-Walli, G. & Frühwirth-Schnatter, S. How many data clusters are in the Galaxy data set?. Adv Data Anal Classif 16, 325–349 (2022).
Statistiques et Probabilités (16 hours of teaching)
Undergraduate Course, Polytech, 2025
An introduction to probability, including the Poisson process and testing theory.
Mesures et intégration (8 hours of teaching)
Undergraduate Course, Polytech, 2025
An introduction to measure theory, including the Lebesgue and Riemann integral.
Statistiques et Probabilités (16 hours of teaching)
Undergraduate Course, Polytech, 2024
An introduction to probability, including the Poisson process and testing theory.
Mesures et intégration (10 hours of teaching)
Undergraduate Course, Polytech, 2024
An introduction to measure theory, including the Lebesgue and Riemann integral.
Analyse de données II (18 hours of teaching from 2024 to 2025)
Graduate Course, Université Clermont Auvergne, laboratoire de mathématiques Blaise Pascal, 2024
Advanced data analysis via PCA, PFA, and k-means.
Outils Mathématiques 2 (22.5 hours of teaching)
Undergraduate Course, Université Clermont Auvergne, laboratoire de mathématiques Blaise Pascal, 2024
An introduction to the basic concepts of mathematics, such as ordinary differential equations.
Stochastic Modelling (60 hours of teaching from 2020 to 2023)
Undergraduate Course, Friedrich-Alexander-Universität Erlangen-Nürnberg, Department of Mathematics, 2020
An introduction to probabilistic models, including the Poisson process and finite Markov chains.
Introduction to Statistics and Statistical Programming (90 hours of teaching from 2020 to 2023)
Graduate course, Friedrich-Alexander-Universität Erlangen-Nürnberg, Department of Mathematics, 2020
Introduction to statistical tests with an emphasis on their theoretic validity. Data analysis via the programming language R.