Program
The aim of the Master of Science in Artificial Intelligence Systems is to provide senior-level executives with high employability in the AI and Data Science fields.
The program will enhance their broad professional skills, including scientific and technological as well as personal and commercial. Emphasis is made to ensure that graduates will have:
- An open-mindedness and curiosity facilitating the understanding of economic phenomena related to globalization.
- A French socio-economic and socio-professional culture,
- An ability to present and defend a project in a variety of complex contexts.
The heart of this program is to train international and national graduates to solve complex problems using AI techniques and tools by gaining a solid background in mathematics and programming skills. A balance of scientific and technical training is offered, updated and supported by continuous research.
Fresh insights are provided to societies and their cultures and to the evolving business environment, providing graduates with a global understanding of the impact of AI techniques, thus guaranteeing them substantial potential for integration and evolution in business.
Semester 1 – Foundation Semester
This semester has two main objectives:
- Unify students’ knowledge, independent of their current level, by establishing a common scientific background in mathematics and programming as a prerequisite for future semesters
- Culturally integrate students, thus reducing their culture shock via French as a Foreign Language (FLE) courses, an integration program introducing French culture and civilization, a coaching program and daily immersion in campus life.
S1 Foundation Semester
| 300 hours | Teaching Unit | Course |
| Big Data Programming | Algorithms | |
| Introduction to Python | ||
| Java & UML Programming | ||
| Relational Databases | ||
| Python & Algorithm Workshop: Initiation | ||
| Cultural Integration | Cultural Integration Workshop | |
| French Language Program FLE | ||
| Managing the Culture Shock | ||
| Foundations of Mathematics | Linear Algebra for Data Science | |
| Numerical Algorithms | ||
| Probability for Machine Learning | ||
| Operations Research I: Linear Programing | ||
| Action Learning | Project I |
Semester 2 – Core Semester
The aim of this semester is for students to understand Artificial Intelligence and the building blocks used to construct its systems. The knowledge and experience obtained in the core semester will enable students to put their knowledge acquired in the foundation semester into action.
S2 Core Semester
| 300 hours | Teaching Unit | Course |
| Cultural Integration | French Language Program FLE | |
| Cross Border Management | ||
| Team Management | ||
| Data Science | NOSQL Databases | |
| Intermediate Python for Data Science | ||
| Operations Research II: Optimization for Data Science | ||
| Machine Learning I: Statistical | ||
| Introduction to Artificial Intelligence | Digital Transformation | |
| Introduction & History of AI | ||
| The Ethics of Artificial Intelligence | ||
| Data Privacy By Design (GDPR) | ||
| Introduction to Artificial Intelligence | ||
| Introduction to Neural Networks | ||
| Action Learning | Project II |
Semester 3 – Excellence Semester
This semester provides students with a panoramic view of all Artificial Intelligence Systems and how to apply them in the various domains of life. Students will acquire the necessary savoir-faire to appropriately use analytical tools in each system. It is perhaps the most appealing semester combining academic action and real-life exposure to AI systems.
S3 Excellence Semester
| 300 hours | Teaching Unit | Course |
| Analytics | Big Data Architecture & Cloud Computing | |
| Data Visualization | ||
| Sparks & Python for Big Data | ||
| Applications of Artificial Intelligence | AI in Signal & Audio Processing | |
| Computer Vision & Image Analysis | ||
| Introduction to Efficient Programming & GPGPU | ||
| Machine Learning for Cloud: Corporate Conferences Week | ||
| Natural Language Processing | ||
| Recommender System | ||
| Cultural integration | French Language Program FLE | |
| Data Science | Tensorflow & Keras for Deep Learning | |
| Deep learning | ||
| Machine Learning I: Statistical | ||
| Machine Learning II: Bayesian & Unsupervised Methods | ||
| Reinforcement Learning | ||
| Action Learning | Application – AI in Cyber Security | |
| Application – AI in Marketing | ||
| Application – AI in Medical System |
Internship
The last semester is a compulsory 6-month internship and is the capstone of the MSc – AIS program. Students will acquire technical business experience, enriched by working in different social and cultural environments, facilitating their future professional integration.
It is mandatory that the mission is part of an industrial or research project. The well-defined role of the student must include active participation in all stages of analysis and design cycles. Business startup projects can be accepted under certain conditions.
Projects are validated by the academic team. Interns will benefit from a well-developed internship agreement insuring compliance with new regulations.
Students of our Master of Science in Artificial Intelligence Systems are paid between €1300 and €2,000 per month during their internships.
