Master in Mathematics, Vision, Learning 12 months Postgraduate Programme By Institut Polytechnique de Paris |TopUniversities
Subject Ranking

# 37QS Subject Rankings

Programme Duration

12 monthsProgramme duration

Tuitionfee

4,317 EURTuition Fee/year

Application Deadline

08 Jan, 2026Application Deadline

Programme overview

Main Subject

Mathematics

Degree

Other

Study Level

Masters

Study Mode

On Campus

As more and more numerical data is used in science, technology and society, there a growing need for top-level researchers in mathematics with expertise in numerical data acquisition, processing and  automatic interpretation. The Mathematics, Vision and Learning Year 2 Master brings together these skills and knowledge with the aim of training tomorrow’s experts. The courses offered are driven by data and problems from the real world focusing on scientific fields and industrial and medical applications. Many mathematical topics are also covered including signal representation techniques, variational methods and partial differential equations in image analysis, compressed sensing, probability learning theory, random matrices, convex optimization, theory of shape space, kernel learning methods, graphic models, Markovian simulation learning, control theory and reinforcement learning.

Programme overview

Main Subject

Mathematics

Degree

Other

Study Level

Masters

Study Mode

On Campus

As more and more numerical data is used in science, technology and society, there a growing need for top-level researchers in mathematics with expertise in numerical data acquisition, processing and  automatic interpretation. The Mathematics, Vision and Learning Year 2 Master brings together these skills and knowledge with the aim of training tomorrow’s experts. The courses offered are driven by data and problems from the real world focusing on scientific fields and industrial and medical applications. Many mathematical topics are also covered including signal representation techniques, variational methods and partial differential equations in image analysis, compressed sensing, probability learning theory, random matrices, convex optimization, theory of shape space, kernel learning methods, graphic models, Markovian simulation learning, control theory and reinforcement learning.

Admission Requirements

90+
6.5+
  • Completion of the first year of Master in mathematics at Institut Polytechnique de Paris or equivalent in France or abroad.
  • Motivated computer scientists with a very good level in mathematics will also be considered.

08 Jan 2026
1 Year
Sep

Domestic
254 EUR
International
4,317 EUR

Scholarships

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