Ects : 6

Enseignant responsable :

• JULIEN CLAISSE

Volume horaire : 15

Description du contenu de l'enseignement :

The Python and PyTorch languages are commonly used to build ML/IA algorithms. The classroom course is complemented by a practical application thesis in economics or finance (e.g. Deep hedging, rapid calculation of expected shortfall, optimal portfolio management, high-frequency trading, solving semi-linear equations of the second order, variance reduction, etc.).

Compétence à acquérir :

• Mastery of Python and PyTorch. Ability to build an ML/IA algorithm.