Welcome

• Cyrille Doux (LPSC)

Basic concepts of statistics - Part I

• Romain Madar (Laboratoire de Physique Corpusculaire de Clermont-Ferrand (LPC))

Basic concepts of statistics - Part II

• Romain Madar (Laboratoire de Physique Corpusculaire de Clermont-Ferrand (LPC))

Classical interval estimation, limits, systematics and beyond - Part I

• Nicolas Berger (LAPP)
• Lydia Brenner (Nikhef National Institute for Subatomic Physics and University of Amsterdam)

Classical interval estimation, limits, systematics and beyond - Part II

• Nicolas Berger (LAPP)
• Lydia Brenner (Nikhef National Institute for Subatomic Physics and University of Amsterdam)

Hands-on: statistics

• Nicolas Berger (LAPP)
• Lydia Brenner (Nikhef National Institute for Subatomic Physics and University of Amsterdam)

Hands-on: statistics

• Nicolas Berger (LAPP)
• Lydia Brenner (Nikhef National Institute for Subatomic Physics and University of Amsterdam)

Pizza discussion: environmental and ethical impacts of AI and good practices

• Steven Schramm (University of Geneva)

Introduction to machine learning

• Vincent Barra (UCA)

Hands-on: Introduction to machine learning tools

• Yann Coadou (CPPM, Aix-Marseille Université, CNRS/IN2P3 (FR))

Anomaly detection

• Emille Ishida (CNRS/LPC-Clermont)

Hackathon

Bayesian inference

• Cyrille Doux (LPSC)
• Florian Ruppin (IP2I Lyon)

Hands-on: Sampling techniques

• Cyrille Doux (LPSC)
• Florian Ruppin (IP2I Lyon)

Introduction to deep learning

• Florian Ruppin (Université Lyon 1 - IP2I)

Hands-on: deep learning

• Florian Ruppin (Université Lyon 1 - IP2I)

Simulation based inference

• Cyrille Doux (LPSC)

Foundation models

• Francois Lanusse ({CNRS}UMR7158)

Farewell

• Yann Coadou (CPPM, Aix-Marseille Université, CNRS/IN2P3 (FR))