University diploma Artificial intelligence and intellectual property distance learning

Public

Targeted audiences for the DU are Master of Laws students, IP law practitioners (European Patent Attorneys, Intellectual Property Lawyers) as well as non-specialists in intellectual property law, such as marketing professionals, project managers, business leaders and anyone interested in artificial intelligence and its relationship with intellectual property.

Prerequisites

A Master's degree first year or equivalent is required as well as a good English level.

Application and admission

An admission committee composed of education officials, assisted by one or two professionals, reviews the application to verify the English proficiency and evaluate the motivation of candidates.

The number of places is limited to 30 people.

Educational objectives

The impact of the development of computer science on the knowledge of law is phenomenal and fundamental. Yet, few lawyers have the expertise to understand the impact of new algorithmic methods in their practice. The objectives of the training are twofold: the first is to transfer knowledge and skills in this high-tech sector, while the second is to provide technical training to lawyers.

The university degree “Artificial Intelligence and Intellectual Property” has, on the one hand, a goal to remedy this lack in the field of intellectual property rights. Indeed, if there are many training courses on the digital and the law, none sufficiently understates the new issues of artificial intelligence in the field of intellectual property rights, in order to understand and control the issues of protection of these new types of creation, their usefulness to the implementation of rights, as well as their technical and economic environment.

Moreover, another specific objective of the training is that it provides an entire module dedicated to computer technology (Module 1: What is AI: Technical introduction and demystification?), including practical work offering exercises on the code, algorithms, data. This gives it some added value and gives it originality compared to other existing training courses in France and Europe. Thus, at the end of the training, the participants will be able to take advantage not only of deep knowledge in law of the artificial intelligence, but also in computer technique.

Download the brochure for the year 2022-2023 by clicking on the image.

Programme

Module 1 : What is AI ? Technical introduction and demystification

  • Acquire the basic principles of computer technology and data science
  • Learn how to write a short program ("hello world"), compile it and run it
  • Learn how to write a short artificial intelligence algorithm in Python
  • Understand, with precise distinction, the various techniques of artificial intelligence and data science

Module 2 : Transverse : AI and the Law

  • Acquire a general legal culture concerning the relations between artificial intelligence and Law
  • Understand the ethical and societal challenges related to artificial intelligence
  • Understand the technical and legal cybersecurity challenges related to AI
  • Understand the challenges of artificial intelligence in terms of fundamental rights

Module 3 : Algorithms and data protection

  • Understand the legal issues related to data protection: business secret, "ownership" of data, rights to personal data.
  • Understand the legal framework related to the circulation of data: free circulation, competition law, open licenses.

Module 4 : Copyright and computer-generated work

  • Develop an in-depth understanding of the various issues related to the protection of artificial intelligence processes by copyright
  • Understand the issues related to the copyright protection of the products obtained by artificial intelligence processes: creativity, protection, ownership of rights
  • Understand the use of artificial intelligence for the enforcement of copyright

Module 5 : Patent law and computer generated inventions

  • Develop an in-depth understanding of all issues related to the patent protection of artificial intelligence applications and their products
  • Understand the use of artificial intelligence, from patent drafting to “patent landscaping”...
  • Understand the use of artificial intelligence for the implementation of patent rights

Speakers

  • Adrien Aulas (Lawyer at the Paris Bar, co-founder of Aeon)
  • Rahul Bhartiya (Leader AI Implementation - EUIPO)
  • Stefano Bianchini (Associate Professor, BETA, University of Strasbourg)
  • Mirko Boehm (Open Source Ambassador at MBition/Daimler. Visiting lecturer and researcher at the Technical University of Berlin, DE)
  • Oleksandr Bulayenko (Researcher CEIPI, University of Strasbourg)
  • Julien Cabay (Researcher FNRS, Associate Professor ULB and ULiège)
  • Maxime Cornet (Doctoral Student, University Paris-Saclay)
  • Thierry Debled (Adjunct Professor at CEIPI, University of Strasbourg)
  • Rapahël Déchaux (Associate Professor, University of Aix-Marseille)
  • Jean-Marc Deltorn (PhD, CEIPI, University of Strasbourg)
  • Estelle Derclaye (Associate Professor, University of Nottingham, UK)
  • Marta Duque Lizarralde (Doctoral Student, Max Planck Inst. Munich)
  • Paul Gagnon (Senior legal counsel, AppDirect, USA)
  • Kim Gerdes ( Associate Professor of Linguistics at ILPGA University Sorbonne Nouvelle - Paris 3)
  • Samir Ghamri Doudane (INPI)
  • Domenico Golzio (Director DG1, European Patent Office, The Hague, NL)
  • Andres Guadamuz (Senior Lecturer at University of Sussex, UK)
  • Dominique Guellec (Scientific Advisor to the Observatory of Sciences and Techniques, Paris)
  • Richard Kennedy (UK and European patent attorney,  partner at Venner Shipley, UK)
  • Natalia Kapyrina (PhD, Lecturer at MGIMO University, CEIPI)
  • Mauritz Kop (IRecht, Stanford Law School TTLF Fellow)
  • Jean Lassègue (Philosopher, Senior Researcher at the National Scientific Research Centre - CNRS)
  • Nari Lee (Professor, Hanken School of Economics, Finland)
  • Franck Macrez ( Associate Professor at CEIPI University of Strasbourg)
  • Gianclaudio Malgieri (Lawyer and post-doctoral researcher, University of Brussels, Sant'Anna School of advanced studies, Pisa)
  • Frédéric Marty (CNRS Associate Researcher, University of Nice Sofia-Antipolis)
  • Mathias le Masne de Chermont (Lawyer at the Paris Bar, co-founder of Aeon)
  • Tobias McKenney (Senior European IP Policy Manager)
  • Kelly Merkel (Senior Intellectual Property Attorney at Michelin)
  • Anke Moerland (Professor, University of Maastricht, NL)
  • Martin Mueller (Chairman, Boards of Appeal, EPO)
  • Carlos Muñoz Ferrandis (Huggingface)
  • Eleonora Rosati (Associate Professor in Intellectual Property Law, Stockholm University)
  • Hugo Ruggieri (Legal Adviser and DPO, Doctrine, Paris)
  • Nicolas Sennequier (INPI)
  • Noam Shemtov (Professor of Law, Queen Mary University, London, UK)
  • Édouard Treppoz (Professor, University of Lyon 3)
  • Assia Wirth (Doctoral Student, University Paris-Saclay)
  • Aleš Završnik (Senior Researcher, University of Ljubljana, Slovakia)
  • Herbert Zech (Professor, Humboldt University, Berlin)

Teaching methods

Distance learning mode :

  • Visual presentation of lectures and discussions
  • Individual follow-up of participants / advice and Q&A between the pedagogical coordinators and each participant.
  • Course materials :
    • Videos
    • Multiple Choice Questionnaires

Course material

The teaching material is accessible on the training's internal online platform.

Type of training and certification

A university degree shall be delivered upon completion of the training and under condition of meeting the knowledge and skills level expected.

Assessment

The evaluation system consists in a continuous assessment where each module has an equivalent coefficient.

The training, divided into five modules, can be followed either in its entirety, giving rise to the university degree, or module by module.

Each module will be sanctioned by a written test, lasting one hour, performed remotely (via the Moodle platform). Each teacher prepares a written test subject, which may include an essay, a technical note, a text commentary, a lecture question, or a case study. Each test gives rise to a score out of 20.

The final validation of the diploma is subject to the passing of a final oral examination, which consists of the defense, in the presence of two jury members, of a case study work on an artificial intelligence application.

A case study of an artificial intelligence application, about ten pages long, is required at the end of the 5 training modules. 

Each module can also be followed independently, without being able to then claim the diploma but a simple certificate of participation (Pass' Compétences).

Registration fees

Registration fees for the academic year 2022/2023

  • Students (Initial training): 1,000 euros.

Every student in initial training at a higher education institution must pay the Campus and Student Life Contribution (CVEC) before enrolling at his or her institution.

This contribution can be paid or waived on the MesServices.Etudiant.gouv.fr website.

  • Professional: (continuing education): 3,500 euros (including university fees)

The training can also be taken in modules (without giving right to a diploma)

Fee for each module (continuing education): 1,000 euros (including university fees)

Duration

The training represents an hourly volume of 120 CM hours per year, carried out remotely (via the Moodle platform).

Each module represents a volume of 24 hours of lectures: 12 hours of personal work and 12 hours of teaching.

For the academic year 2022-2023, teaching will take place according to the following calendar (hours are CET) :

  • Module 1 : 

4-5 November 2022 : hybrid (Strasbourg / Zoom), 9:00-12:30 / 14:00-17:30

2-3 december 2022 : hybrid (Strasbourg / Zoom)  9:00-12:30 / 14:00-17:30

Exam : 16 December 2022, 18:00 - 19:00 (online)

  • Module 2 :

2-7 January 2023 : online, 18:00 - 20:00 (Saturday: 10:00 - 12:00)

23-28 January 2023 : online, 18:00 - 20:00 (Saturday: 10:00 - 12:00)

Exam : 10 February 2023 : online, 18:00 - 19:00

  • Module 3 :

27 Febr. - 4 March 2023 : online, 18:00 - 20:00 (Saturday: 10:00 - 12:00)

13 - 18 March 2023 : online, 18:00 - 20:00 (Saturday: 10:00 - 12:00)

Exam : 31 march 2023, 18:00 - 19:00

  • Module 4 : 

3-8 April 2023 : online, 18:00 - 20:00 (Saturday: 10:00 - 12:00)

24-29 April 2023 : online, 18:00 - 20:00 (Saturday: 10:00 - 12:00)

Exam : 12 May 2023, 18:00 - 19:00

  • Module 5 : 

22-27 May 2023 : online, 18:00 - 20:00 (Saturday: 10:00 - 12:00)

5-10 June 2023 : online, 18:00 - 20:00 (Saturday: 10:00 - 12:00)

Exam : 23 June 2023, 18:00 - 19:00

  • Submission of case studies titles: 30 June 2023
  • Deadline for submission of completed case studies : 3 September 2023
  • Retake exams : 9 September 2023 (online)

Timetable

6pm to 8pm CET during the week, 10am to 12pm CET on the Saturday.

This schedule is given on an indicative basis and can slightly change.

Location

  • Module 1: hybride
  • Modules 2 to 5: Remote training.

Heads of studies

Jean-Marc DELTORN

Researcher at CEIPI, University of Strasbourg

Franck MACREZ

Associate Professor at CEIPI, Director of the Research Department of the CEIPI, University of Strasbourg

Information and registration

Registration for the 2022-23 edition of the diploma is closed.

For any other administrative or academic information, please send an email to: registration_duaiip_2223[at]ceipi.edu

or Tel: +33 (0)3 68 85 80 27

Fields

Intellectual property
Industrial property
Artificial intelligence