Descriptif
Instructors:
Julien Prat (CNRS, CREST, ENSAE and Ecole Polytechnique)
Daniel Augot (INRIA and Ecole Polytechnique)
Format: 24 hours
Summary:
The digitization of markets is proceeding at an ever-increasing pace, deeply transforming how
customers shop for products and services, but also how firms interact with one another. The
design of internet platforms and Blockchain protocols raises new challenges that can only be
grasped through a sound understanding of computer science and economic incentives.
We will explore the economic concepts (market design, pricing mechanisms…) and computer
science tools (interface design, blockchain protocols...) students need to acquire in order to
participate to this transformation. The course will put an emphasis on Blockchains because of
their disruptive potential, thus preparing students for the next wave of innovations.
The material will be conveyed through a combination of lectures and seminars. In order to cover
the width of the field, we will invite academics but also experts working in the private sector
(e.g. Capgemini, PwC…) as well as startup founders. Hence the course will combine theoretical
insights with hands-on experience and case studies.
The composition of the class will reflect the interdisciplinarity of the topic by bringing together
students from computer science and economics. Students will form teams and elaborate an
original platform or blockchain design, using the analytical tools and returns of experience
presented during the course. Each project will be concluded by a pitch in front of experts who
will assess its strengths and areas for improvements.
On completion of this course, students should be able to
Assess the commercial soundness and technological underpinnings of a specific
platform design;
Determine whether decentralization is desirable and how it can be achieved through
recourse to Blockchain technology;
Evaluate the business needs of companies and identify the best ways to answer them;
Discover the appropriate design to address governance problems and economics
tradeoffs;
Anticipate the ethical and legal issues raised by each project.
effectifs minimal / maximal:
/20Diplôme(s) concerné(s)
- M2 Data AI - Data and Artificial Intelligence
- MScT-Economics, Data Analytics and Corporate Finance
- M2 Cyber - Cybersecurity
- Echanges PEI
- Titre d’Ingénieur diplômé de l’École polytechnique
Parcours de rattachement
Format des notes
Numérique sur 20Littérale/grade réduitPour les étudiants du diplôme M2 Data AI - Data and Artificial Intelligence
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme Titre d’Ingénieur diplômé de l’École polytechnique
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme Echanges PEI
Le rattrapage est autorisé (Note de rattrapage conservée)Pour les étudiants du diplôme MScT-Economics, Data Analytics and Corporate Finance
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 4 ECTS
La note obtenue rentre dans le calcul de votre GPA.