French

Artificial intelligence (AI) is a rapidly growing interdisciplinary field, driven in particular by proven successes in image processing and natural language handling. successes in image processing and natural language processing. In its entirety, it offers the In general, it offers the possibility of responding to a strong need of industrialists who are seeking to make the best use of data. This may involve gaining a better understanding of complex systems or predicting their behaviour, with the aim of increasing the competitiveness of companies.

As a student in the MSc Data Sciences & Artificial Intelligence course at Université Côte d'Azur, you will be trained to become a specialist in the mathematical techniques and computational tools needed to extract knowledge from large amounts of data. Students will receive a thorough grounding in theory as well as technical and practical data science skills, enabling them to apply advanced data science methods to real-world problems.

The MIAGE IA2 course trains computer scientists capable of implementing in a very concrete way the various techniques resulting from artificial intelligence (AI).
At the end of this training, they will be able to :

• decide if a problem is related to an AI technique,
• know the limits and constraints associated with each AI technique,
• develop an AI application using existing libraries or cloud services.

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.