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ACADEMIC PREREQUISITES
Mathematics and Computer Science Background
Applicants should have a strong academic background in both Mathematics and Computer Science. A Bachelor's degree in either field is welcome, provided the applicant demonstrates solid proficiency in the other.
Applied Mathematics
A solid understanding of linear algebra, partial derivatives, and multiple integrals for mathematical modeling is required. Familiarity with statistics and signal/image processing concepts, especially Fourier theory and basic filtering techniques. While many software libraries implement these functionalities, a firm grasp of the underlying theories and their practical applications is important.
Computer Science
Applicants should have completed at least one course covering Algorithms and Data Structures and demonstrate programming proficiency, particularly in C++ and Python.
Portfolio, GitHub & Personal Projects
Applicants are strongly encouraged to provide evidence of their technical, scientific and creative work.
- Online Portfolio (highly recommended): Showcase your best technical, scientific or creative projects through visual results, videos, interactive demonstrations or research work. Clearly identify your personal contributions.
- GitHub or Equivalent (recommended): Share code repositories demonstrating programming skills, software engineering and experimentation.
- Personal & Academic Projects: University projects, research prototypes, creative work, hackathons or independent developments.
The quality and relevance of your work matter more than the number of projects.
Internships & Professional Experience
Previous internships, research activities and professional experience are highly valued.
Experience in computer graphics, computer vision, AI, software engineering, VFX, animation, video games, filmmaking or other related technical and creative fields is particularly relevant.
Applicants should highlight:
- Internships and professional placements, including their duration and responsibilities.
- Research experience, whether academic or industrial.
- Technologies and tools used in real projects.
- Concrete achievements, technical challenges and individual contributions.
Previous professional experience is a significant asset, but is not mandatory for admission.
Direct Entry to the Second Year (M2)
Direct admission to the second year of the Master's (M2) is possible through established partnerships, such as with Ecole polytechnique, Telecom SudParis and Telecom Paris, or by demonstrating a strong technical background and demonstrated proficiency in areas closely aligned with the M1 curriculum. Applicants must provide evidence of their proficiency in the relevant subjects, ensuring they meet the academic and technical requirements of the program.
