Curriculum "Data Analytics for Business"

Semester 1 

• Strategic thinking
• Financial performance
• Data management
• Generative bootcamp (artificial intelligence)
• Public speaking
• Visual communication & sustainable impact 

Semester 2 

• Business & socio-ecological transitions
• Sustainable environment for organisations
• Team management
• Business & sustainability
• Human & AI collaboration
• Business & climate change
• Open Innovation Challenge (corporate project)

Pre-specialisation courses

• Marketing reconsidered
• Procurement
• Fundamentals of digital analytics for business

Additional content

• 4- month internship (in France or abroad) or academic partnership

SEMESTER 1

• Code bootcamp
• Digitalisation of companies
• Data management
• Impacts of artificial intelligence
• Data visualisation
• Machine learning I: fundamentals

SEMESTER 2

• Agile project management
• Machine learning II (advanced techniques)
• Business analytics
• Stochastic processes
• Business and Artifical Intelligence (AI)
• Change Management

• International internship
• Final dissertation
• Study trip to Paris
• Hackathon (CGI, Arval, Microsoft)
• Certification: Microsoft Azure AI-900
• Certification PSM I: Professional Scrum Master
• Conferences (Cdiscount, Nestlé)

Degree requirements:

All degree requirements must be successfully completed. The awarding of the diploma will be confirmed by the examination board.

Assessment methods:

Evaluation methods may include a variety of approaches such as case studies, presentations, practical exercises, written tests, group projects, and oral assessments. These diverse methods allow for a comprehensive and in-depth evaluation of the skills and knowledge acquired.