Management and AI - 350 - 2nd year Master's degree

Syllabus

Bloc compétences technologiques

Bloc Compétences Droit/Économie/Régulation/Éthique de l'IA

Bloc Compétences économie et management des IA

Bloc Séminaires de spécialité / Cycles de conférences (3 UE à choisir)

Bloc Professionnalisation

Academic Training Year 2025 - 2026 - subject to modification

Teaching Modalities

The Master's degree comprises 476 hours of tuition, starting on September 1. The Program is based on a combination of theoretical instruction, professionalization and practical application.

Skills development is based on a pedagogical approach that alternates theory, real-life situations and case studies, thanks to a diversified approach that includes hackathons, active teaching and conference cycles. In this way, skills are applied concretely to ensure that learners acquire them properly. In terms of pedagogy, the Program places particular emphasis on the application of the knowledge and skills acquired in the classroom.

The program is divided into 4 main areas.

  1. Technological: Data sciences and AI.
  2. Governance, law and ethics.
  3. Economics and management of information and innovation.
  4. Business applications

Work-study schedule: The Program begins on September 1 for one week at the university, then 2 days at the university / 3 days at the company until mid-June.
This is an apprenticeship program, with no internship. A research paper structures and finalizes the student's academic path.

Activities:

  • Translate business challenges into AI-based problems and solutions.
  • Develop technical specifications based on strategic and operational requirements.
  • Design, manage and develop AI projects.
  • Plan the testing and validation process for AI models.
  • Deploy AI solutions.
  • Monitor, maintain and optimize solutions based on AI technologies.
  • Collect, analyze, store, secure and prepare large volumes of data for learning, testing and inference.
  • Produce results reports on AI projects.
  • Collaborate with business experts and manage multidisciplinary, multi-profile teams.
  • Communicate with internal and external stakeholders.
  • Maintain a technology and market watch on the AI ecosystem.
  • Ensure compliance with current regulatio ns and environmental, ethical and legal issues.
  • Audit AI systems.

Research Support

 

Research-driven Programs 

Training courses are developed in close collaboration with Dauphine's world-class research programs, which ensure high standards and innovation. 
Research is organized around 6 disciplines all centered on the sciences of organizations and decision making.

Learn more about research at Dauphine