v2.11.0 (5509)

Master - M2 Machine Learning, Communications and Security


The second year of the Machine Learning, Communications, and Security Master’s program (MICAS) is devoted to information sciences and explores solutions to efficiently process, transmit, store, and protect information. This cross-disciplinary program starts with foundational courses in information processing, building around three main areas: machine learning, communications theory and technologies; and security.

This research-oriented program provides students with strong academic training in data processing and an in-depth knowledge of communication technologies, machine learning algorithms and information security methods. The first semester encompasses courses taught by faculty members from three Institut Polytechnique de Paris laboratories. During the second semester, students will complete an internship for a minimum four-month period.

This second-year Master’s program offers mathematically-minded students a strong background in the fundamentals of information processing and related technologies, preparing them to pursue a career in academia or industry.

This program aims to:

  • Provide students with a mathematical and practical background in information processing concepts and tools with state-of-the-art applications related to learning, communications and security
  • Enable students to identify complex problems in these fields, understand their interactions, and demonstrate solutions through performance and limitation assessments
  • Prepare students to pursue careers in a wide array of domains in industry or academia

domaines d'enseignement



Students graduating from this program will be able to:

  • Pursue a research or development career in a higher education institution or industry in a wide range of fields including Information and Communication Technologies (ICT), biology, healthcare, energy, transportation, and manufacturing
  • Pursue a PhD enabling them to then occupy positions such as researchers and project managers in R&D companies or research fellows and professors in academic institutions


Unités d'enseignement

UE Type d'enseignement Domaines Catégorie d'UE Credit Ects Volume horaire Responsables Periode de programmation Site pédagogique
MAP566 Statistics in Action PA - C5B Mathématiques appliquées UE de base. 3 Julien Chiquet X-AN3-P2
MAP566A Introduction to Machine Learning Cours scientifique Mathématiques appliquées 56 Eric Moulines,
Gabriel Stoltz
Veuillez patienter