Teaching
Course materials for statistics, financial analysis, and more.
I teach at ESSCA (statistics & information systems) and INSEEC (financial analysis, graduate level). Course materials live here and are updated each semester.
Annotating Course Pages
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Undergraduate
Probabilités & Statistiques
ESSCA
An introduction to probability and statistics as tools for modelling uncertainty and making sense of data. Covers continuous random variables, classical distributions, convergence theorems (LLN, CLT), and both descriptive and inferential statistics.
“Tous les modèles sont faux, mais certains sont utiles.” — George E. P. Box
Mathematical Analysis
ESSCA
Differential calculus and optimization for economics and management: univariate and bivariate derivatives, elasticity, local extrema, Hessian-based analysis, and an introduction to linear programming.
Graduate
Financial Analysis
INSEEC · MSc
A deep dive into financial and strategic analysis: diagnosing financial statements (individual and consolidated), profitability, solvency, capital structure, and return metrics (ROCE, ROE). Covers both listed and unlisted companies, with real-world case studies.
Part of the Expert en Stratégie Financière (RNCP40177) programme.
AI Guide
Foundational AI Papers
A paper-centric guide from McCulloch & Pitts (1943) to DeepSeek-R1 (2025), covering the key ideas and breakthroughs in artificial intelligence, from machine learning, deep learning, and transformers explained through the landmark papers that introduced each idea.