The 2nd year courses of the IARF speciality are common to those of the engineering course of the Master's degree in Real Time Systems Engineering Robotiquet and of the EEA (Electronics, Electrical Engineering, Automation) mention.

The IAAA course introduces the most recent advances in artificial intelligence and trains students to exploit the associated methods and techniques in innovative applications. The themes covered are machine learning, deep learning, automatic natural language processing, modelling and solving problems based on constraints, and knowledge representation and processing. These topics are particularly relevant to data science and fundamental computer science.

Data is everywhere, increasingly large and complex, coming from various sources such as computers, mobile devices, sensors and social networks. This data is creating new needs and emerging applications that require advanced techniques related to various domains such as Big data, semantic web, internet of things, analytics and data science etc.  It is about managing large, dynamic and varied data that can be linked by complex relationships. The classic functionalities of traditional enterprise information systems are inadequate and insufficient to meet these needs effectively.

This course aims to provide computer scientists with a specialisation in the field of digital imaging. Its particular interest is to deal with : - the design and implementation of image-based applications (production, analysis and transmission of images, virtual reality, 3D animation). - the development of solutions dealing separately or simultaneously with image analysis and synthesis, 3D reconstruction, animation, virtual reality, augmented reality, with the help of artificial intelligence tools.

A natural evolution of the projects carried out in recent years by data science and big data, what is most often referred to as artificial intelligence goes further both in terms of technological requirements and in the broad spectrum of scientific fields concerned: robotics, human-machine interaction, language processing, etc.

Big Data is a strategic priority for businesses of all sizes and sectors. It is a revolution that is bringing sweeping changes to companies and is seen as an essential tool to create value.

Télécom Paris Tech leads three teaching and research chairs related to Big Data, offers a wide range of initial and continuing training programs, and promotes innovation through its incubator, Télécom Paris Novation Center. This brings together approximately fifty research professors, fifty PhD students and about one hundred graduates per year.

The rapid growth of the internet has led to vast amounts of data being collected. As analyzing this data requires tremendous computing power, high-performance data analytics employs various parallelization techniques to reduce the execution time. These techniques can be applied to various domains such as high-performance computing, artificial intelligence and big data.

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.