Laboratoire d'Expérimentation en Sciences Sociales et Analyse des Comportements

Facebook          YouTube    

A Data Science track


This track is available over the 3 years and culminates with the MSc in Data Science and Organizational Behavior.


Compulsory Classes (first term): Organizational Behavior (in the experimental lab), Statistics and Data Processing, IT Tools.

Optional Classes (second term):

VBA - The course teaches students to think algorithmically and solve problems effectively. Mastering VBA is now a requirement for many careers, particularly in the field of finance. Students will learn the basics of language and create their own functions.
SQL and databases - Databases are at the heart of information systems. Much of the organizations' data is stored in databases. Data managers or specialists must transform this data into actionable knowledge. This course teaches everything you need to extract and manipulate data and to work with these databases.
Game theory - Game theory is the analysis of situations in which a decision-maker's gain depends not only on his own actions but also on those of others. Game theory has applications in several fields, such as economics, politics, law, biology and computer science. 


First term: Big Data and Organizational Issues

Second term:

Experimental Economics, Markets and Negociation - This course aims at presenting the main economic and behavioral theories of negotiation and auctions, along with practical applications in experimental economic games for organizations. The course will provide the basics: representing games and strategies, the extensive form (which computer scientists call game trees), Bayesian games (modeling things like auctions), repeated and stochastic games, and more. We'll include a variety of examples including classic games and applications to organizations. We study the strategic reasoning of agents involved in bargaining situations and analyze the factors that influence these decisions (rules, order of decisions, impatience, risk attitudes, outside options, etc.). We pay specific attention to the behavioral biases that usually arise in bargaining, such as the winner's curse, over-bidding, emotions, etc.


Business Intelligence - After this module, the student should be able to understand the purposes and techniques of economic intelligence, identify relevant sources of information, analyze collected information, and use it in decision-making processes. Learning objectives:  Be able to monitor the legal, economic and financial environments of international business and turn the collected data into operational information.

Data Science - This course is relevant for managers because in their everyday work they are expected to properly and logically collect, present and describe information, to form conclusions about large populations based only on information acquired on limited samples, to obtain good forecasts and to know how to improve managerial processes.  Therefore, the structure and the content of this course will be built in order to give them these tools. The learning methods will be based on understanding and interpreting concepts and tools.The class is bases on learning R.

MSc Year (3rd YEAR):

To train future leaders and academics in data and behavior management to a high level of expertise in the intersection between management, behavioral tools and data science.
The programme is created to give students programming skills, both by syntax (IT tools) and module (games tools), which is a unique way of teaching the subject.