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Aerospace Education Catalogue

Master Machine learning, Intelligence artificielle et Données (MIND)

  • Organisation: Sorbonne Université - Faculté des Sciences et Ingénierie
    (Sorbonne Université)
  • Type of Course: Initial education
  • Language(s): French
  • Place: Sorbonne Université (French Regions: Ile-de-France)
  • Prepared diploma/grade/title: Master or DNM: French National Master Degree
  • Level of entry: French Baccalaureat + 3
  • This training is included in RNCP / RS

Course Details

Objectives: The MIND course (previously called DAC) aims to train experts in the fields of data science and artificial intelligence. The course is structured around three main skill profiles: big data (database, distributed algorithms and scaling), statistical learning (machine learning, deep learning, generative AI) and symbolic learning (deduction, causality, classical formal logic and fuzzy logic).

Degree Level (EU) : 7 - (EQC level or equivalent)

Acquired skills during the training : - Know and implement the principles of managing structured or unstructured databases.
- Create, manage and operate databases, ensure the quality of these databases to guarantee reliable access to data.
- Collect, pre-process, analyze and process data
- Master digital tools and reference programming languages ??in AI
- Select and implement machine learning and deep learning algorithms for a given problem.
- Mathematically model an AI problem in order to solve it.
- Understand a problem or business issue in order to identify the needs in data science, AI and databases.
- Implement and deploy data science methods in the business context to meet the expectations of the sector of activity.
- Evaluate the performance of an AI system in relation to business objectives.
- Explain an AI system.

Dedicated web site: https://sciences.sorbonne-universite.fr/formation-sciences/masters/master-informatique/parcours-mind

Disciplines

  • Engineering Sciences
  • Applications, Operations

Topics

  • 11 - Data Sciences: Applied Mathematics, Signal and Image Processing, Cryptography, Artificial Intelligence (machine learning, big data, etc.), Computer Science, Cloud, Software Engineering, Virtual Reality, Virtualization, Digital Twins, Metaverse, etc.