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Computer Science for Networks

The second-year Computer Science for Networks (CSN) Master’s program enables students to understand, analyze and improve communication networks, as well as develop and define software for next-generation networks. It provides techniques and tools to tackle current questions through the in-depth study of computer science and complex networks. Students will also learn to master recent approaches based on advanced software engineering.

Parallel and Distributed Systems

Parallel and distributed systems are ubiquitous in many applications in our daily life including AI, online games, social networks, web services and healthcare simulations. These systems distribute computation over many computing units because they have to sustain massive workloads that cannot fit into a single computer. Designing efficient, easy-to-maintain and correct parallel and distributed systems is challenging – a challenge inherent to the complexity of managing multiple machines, many users and very large data sets.

Data Science Starter Program

With the explosion and profusion of data available in a large number of fields, new collection and analysis techniques are having a profound effect on all sectors of economic life, but also on certain research sectors. The course offers an introduction to the best methodological tools for understanding and exploiting data, particularly massive data (Big Data). An immersion in the world of data through an intensive course on the fundamentals of data science.

Artficial Intelligence & Business Transformation (AIBT)

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Artificial Intelligence Internals (168 heures) Montée en compétences techniques en IA : Gestion des masses des données et apprentissage automatique  (Data Integration and Exploration, Big Data Processing, Optimization topics  for AI, Machine Learning and Data Analytics, Sequential Decision Making in AI,  AI certification, robustness and dependability).

Valuation of massive data

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The aim is to train professionals with advanced skills in computer science, optimisation and data science for the valorisation of data deposits.

The training will address the technical and legal aspects, thus meeting the expectations of the following professions: data scientist, data engineer, data manager, data analyst, project manager, decision support engineer, quality control manager.

The originality of the training is to address a broad spectrum of skills in computer science, data science and optimisation.

Advanced Systems and Robotics (SAR) course

The SAR training aims to train specialists in the design, modelling, analysis, optimisation and control of complex robotic systems. It covers the wide range of research and development needs related to advanced "mechatronic" systems in sectors ranging from the mechanical and mechatronic production industry to the land and air transport industry, as well as the health technology sectors.

Intelligent Systems Engineering (ISI) course

The development and implementation of intelligent systems and robotic machines, from the processing of sensor output to its high-level interpretation by artificial intelligence methods, meets a growing need of industrialists in sectors with high employment demand. The ISI course aims to train students in research and development in the fields of intelligent systems and robotics, and in particular on subjects such as multimodal interaction, image and sound analysis, and the design and control of robotic systems, at the interface of computer science, electronics and mechanics.

PARCOURS PERFORMANCE IN SOFTWARE, MEDIA AND SCIENTIFIC COMPUTING (PSMSC)

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This international master track titled 'Performance in Software, Media and Scientific Computing' or PSMSC is a one-year programme taught by the University of Toulouse. It prepares master students for top level careers or PhD programs in several application domains that require use of hardware, software and programming techniques to accelerate data-intensive computations and ensure reliable execution of cutting-edge applications.

Master 2 IISC - Artificial Intelligence and Robotics (IAR)

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The training aims to acquire scientific bases in artificial intelligence and robotics, a general culture in cognitive sciences and neurosciences for the "intelligent" and "bio-inspired" processing of information: 

  • neural network models, 
  • optimization algorithms, 
  • new techniques for man-machine interface, 
  • embedded computing and bio-inspired robotic control.