Teaching

Introduction to linguistic through data science

CPES 2 - Sciences des données, arts et cultures - Université PSL

Course description:

There are more than seven thousand living languages in the world. Before computers became widely used, it was hard to study linguistic diversity on a large scale. The amount of data was simply too great for one person to handle without digital tools.

Nowadays, linguistic databases such as Grambank or Leixbank bring together information on many aspects of natural languages, including phonetics, morphology, and syntax. As a result, the language sciences have been deeply transformed.

This course has two objectives. First, it introduces students to the central questions in contemporary linguistics. Second, it shows them how to use the wealth of freely available databases that make quantitative linguistic research possible.

Link to course materials:

https://github.com/alexeykosh/intro-to-ling-2026-S3

Cultural evolution and computational sociology

Master 2 IA & Society — Paris School of AI (PSAI), Université PSL

Course description:

Culture, defined here as any socially transmitted information, is present not only in humans but also in other animals. What processes govern the transmission and spread of cultural traits, such as languages, behaviours and traditions? What mechanisms drive cultural change over time?

The goal of this course is to introduce students to the diverse field of cultural evolution. Students will become familiar with its main concepts, theories and methods, ranging from mechanisms of social learning and cultural transmission to agent-based modelling and theories of language origins.

Link to course materials:

https://github.com/alexeykosh/cultural-evolution-2026-S3

Behavioral and social sciences: Applications

Master 1 IASO — Paris School of AI (PSAI), Université PSL

Course description:

Modern quantitative, and even qualitative, research demands rigorous practices to make a truly valuable contribution to science. Knowing how to choose a study design, collect and preprocess data, select appropriate statistical methods, preregister a study and deliver the results in a fully reproducible package is an essential skill.

The goal of this course is to teach students the methods and philosophy behind modern research practices. Course contents will include preregistration, basic and advanced statistical methods, experimental designs, reproducibility workflows and other topics. At the end of this course, students will be able to design and implement complex quantitative studies from scratch on their own.

Link to course materials:

https://github.com/alexeykosh/2026-behavioural-and-social-sciences-methods