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.

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.

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).

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.

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.

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.