Cognitive modeling, neurotheory & AI

M1 S1 Courses 

• Cognitive models and artificial intelligence, by A. Cayco Gajic
• Mathematical tools for data science, machine learning, and statistical modeling, by A. Cayco Gajic

M1 S2 Courses

• Computational neuroscience methods, by S. Ostojic
• Computational neuroscience, by B. Gutkin
• Understanding human behavior with cognitive models, by V. Wyart

M2 S3 24-25

• Interplay between deep learning and cognitive science
• Machine Learning for Cognitive Sciences: Princip. and Appl.
• Robotic modelling approaches to cognitive sciences
• Theoretical Neuroscience

M2 S3 25-26

• Action, decision, volition, by E. Koechlin
• Interplay between deep learning and cognitive science, by L. Bonnasse-Gahot
• Learning and decision making, by S. Palminteri & M. Lebreton
• Machine cognition, by E. Chemla, V. Wyart & S. Palminteri 
• Machine learning: principles and applications, by S. Cocco
• Theoretical neuroscience, by J. Ranft et S. Ostojic
• The bayesian brain, by F. Meyniel

ENS-PSL minors:

Beyond their master's degree, students interested in cognitive modeling, neurotheory and AI can complete any ENS-PSL minor of their choice, including the following:

• DATA science (contact: V. Wyart)
• Deeptech and Innovation
• Digital Humanitie