Teaching Materials

Public courses, ebooks, and learning platforms. For the full teaching record, see the CV.

2025 In development

Voir clair en mathématiques (en français)

MOOC · University of Geneva

Open online course on mathematical intuition, approximation, and optimization, designed for a broad audience.

With Prof. H. Duminil-Copin & Dr. M. Karemera (project lead) · supported by the University of Geneva Rectorate

Fall 2025

An Introduction to Data Science using Python

Master's · University of Geneva

Graduate course on data science with Python — pandas, exploratory analysis, visualization, statistical inference (t-tests, ANOVA), and linear regression.

With Dr. Sébastien Biass · course materials →

2021 – present

Introduction à la Statistique (en français)

Undergraduate · University of Geneva

First undergraduate course in statistics — probability, random variables, distributions, estimation, confidence intervals, and hypothesis testing. Built around an AI-powered interactive learning platform.

AI tutor
context-aware chatbot with three interaction modes
Interactive quizzes
weekly exercises with instant feedback
Slide Q&A
per-slide questions and targeted answers

With Dr. M. Karemera, Dr. S. Orso, L. Voirol & S. Feser · visit the platform →

2021 – present

Data Analytics for Pharmaceutical Sciences

Graduate · University of Geneva

Graduate-level course on statistical methods for pharmaceutical sciences. Hands-on, built around real-world examples and an interactive learning platform based on real data.

With Prof. D.-L. Couturier & Dr. Y. Zhang · course materials →

2020, 2025

Inference for Large-Scale Time Series

Graduate · EPFL

Graduate course on the generalized method of wavelet moments (GMWM), with applications to sensor fusion and inertial navigation. Also serves as an introduction to the GMWM R package.

With Dr. D. A. Cucci & Prof. J. Skaloud · course website →

2014 – present

Applied Time Series Analysis with R

Graduate ebook · UIUC, Penn State, UNIGE

Graduate-level ebook on time series methods with R, with a focus on practical implementation and worked examples.

With Prof. R. Molinari, Prof. H. Xu & Dr. Y. Zhang · read online →