The study of AI generally requires knowledge in mathematics, engineering and computer sciences at the bachelor's level. After the first year of undergraduate studies, students can study AI methods and applications through various bachelor’s degree in computer science, mathematics or engineering. Furthermore, from 2022/23 a minor option in Data Sciences will be available to all students allowing them to develop their AI skills.
Computing manifestations are numerous, from our private sphere to industrial applications: social networks, mail, games, banks, office systems, database managers, internet and telecommunications, embedded control systems, avionics, etc.
Faced with these vast societal needs, the Bachelor of Computer Science aims to provide students with abstract and technical skills as well as the knowledge of tools that will allow them to be an actor in the development of this complex and multifaceted field that is computer science.
This program provides a solid foundation of knowledge and skills in mathematics, to train students for the many professions that use mathematics
After the first year, students can enroll in this degree program providing them training for the many professions that use mathematics, either directly or after continuing their studies at Master's level or beyond. The teaching provided is based on more than 150 teacher-researchers who cover all fields of mathematics and its applications. Cross-disciplinary skills (English, computer skills, independent work) and international mobility are valued.
The combination of these two disciplines provides powerful tools that are more than ever needed to solve increasingly complex problems, including new issues emerging at the frontiers of science and technology.
This combination develops abstraction, analysis and technological skills, all of which are highly valued in scientific and professional environments. This program is aimed at students with a high academic potential, who are particularly motivated to follow a demanding and rigorous scientific training, which will increase their autonomy of work, their entrepreneurial spirit and their taste for contemporary science in a university setting.
A transdisciplinary academic program under construction and available from September 2023
This option relies of Sorbonne University’s major-minor educational structure, which enables students to obtain a diploma in a major discipline along with solid grounding in a minor discipline in a related or complementary theme. The Data minor will be available to all students registered at the Faculty of Science and Engineering. Supported by SCAI and the Institute for Computing and Data Sciences (ISCD), it will bring a basis of major skills to those who are destined for scientific master’s degrees related to data and artificial intelligence.
Sorbonne Université and its community currently offers eight master's programs in computer science, mathematics, statistics and robotics, gathering more than 300 students.
Distributed AgeNts, Robotics, Operational Research, Interaction, Decision
The Androide specialty provides both theoretical and practical education covering all areas of Artificial Intelligence, Decision, Operational Research and Interaction.
This covers issues related to "problem solving" that economic actors face, as well as questions related to the implementation of intelligent interaction processes, whether involving a human user or between autonomous entities. Its goal is to educate specialists in Information and Communication Sciences and Technologies, and mastering the concepts, models and tools of these themes.
Master Data Science Paris
This covers issues related to "problem solving" that economic actors face, as well as questions related to the implementation of intelligent interaction processes, whether involving a human user or between autonomous entities.
The DAC specialty provides students with fundamental knowledge of databases as well as processing, collection, manipulation & management of large amounts of data. It naturally relies on state-of-the-art techniques in data mining, artificial intelligence and computational intelligence, with a focus on machine learning (statistical and symbolic, using imperfect datasets).
Learning & Algorithms
The Learning and Algorithms specialty (M2A) offers dual education in mathematics and computer science, focusing on data science and artificial intelligence.
It was started in 2019 and offers a comprehensive understanding of mathematical tools and methods involved in statistical learning, deep learning and artificial intelligence.
Intelligent Systems Engineering
The ISI specialty prepares students for R&D-oriented careers in manufacturing or mobile robotics and on advanced automatic systems.
It covers several themes, such as the perception of the environment, the analysis of scenes, the strategy of problem solving and mechanics. Possible applications include intelligent cars, human-machine interfaces, detection systems, and the analysis and interpretation of signals (such as physiological, audio, video).
The M2 Statistics is a course in mathematical statistics, machine learning and data science at Sorbonne University, hosted by the Laboratoire de Probabilités, Statistique et Modélisation (LPSM).
The M2 Statistics aims to train tomorrow's data scientists by offering a wide range of courses from statistical learning to mathematical statistics, covering a variety of topics from the foundations of statistical theory to the practice of data science.
Advanced Systems and Robotics
This specialty deals with modeling and control problems of mechatronic and robotic systems, the perception of their state and their environment as well as the planning of movements and actions.
In addition to the problems of industrial robotic manipulators, teaching is also provided on issues of service robotics (Automated Guided Vehicle AGV, drone, humanoid, etc.).
Acoustics, Signal processing, and computer science applied to music
The program is designed to provide the scientific fundamentals and musical knowledge necessary to carry out research in the fields of musical acoustics, sound signal processing, and musical informatics. The program’s originality lies in its multi- disciplinary nature; students are required to have a high level of scientific expertise and an understanding of artistic creation.
ATIAM offers a scientific approach to the entire chain of sound and music computing from the physical and psychophysical dimensions to digital modeling and high-level symbolic structures.
IMAGE, COMPUTER VISION, COMPUTER GRAPHICS
The Image (IMA) programme aims to provide in-depth training in the fields of image processing and analysis, computer vision and computer graphics.
The IMA course aims to provide students with an in-depth training in the fields of image processing, computer vision and computer graphics. It combines in its courses coherent arrangements ranging from the foundations of the discipline to the most advanced techniques.
Complex System Engineering
The objectives assigned to the UTC-ISC Master’s degree are to provide future engineering managers with a solid scientific and technological knowledge base to be able to study (viz., to characterize and understand), model and design complex and innovative systems using a systemic multidisciplinary approach.
In this degree, two specialties are offering training related to AI:
Statistical Engineering and Data Science
This program hosted by the Statistical Institute of Paris University (ISUP) is a 2-year high-level training for careers as statisticians and data scientists in innovative sectors.
This program hosted by the Statistical Institute of Paris University (ISUP) is a 2-year high-level training for careers as statisticians and data scientists in innovative sectors. The students can follow the second year working part-time as members of the Training Center for Apprentices (CFA). In this program, academics and private sector employees teach statistics and computer science.
A transdisciplinary minor at the Master's level will soon be made available to all 3 faculties at Sorbonne University.
This minor will enable SU students in the humanities (including but not limited to digital), medicine and science to acquire the necessary computer and mathematical knowledge to understand AI.
It will teach key concepts to grasp the challenges of AI applications and developments in their respective disciplines.
The project will be set up by a multidisciplinary teaching team bringing together colleagues from the fields of humanities, medicine and science from September 2022.
SCAI regroups a total number of more than 100 PhD supervisors in AI (with research habilitation or HDR). They have successfully supervised more than 380 PhDs in the past 5 years. Overall, they work in more than 20 laboratories in which they are part of teams studying all aspects of modern AI, from statistics to social sciences.
Broadly, Sorbonne University doctoral landscape is organised in 23 Doctoral Schools gathered into a Doctoral College in charge of coordinating Sorbonne University doctoral policy. http://ifd.sorbonne-universite.fr/fr/index.html
The doctoral school is responsible for all matters related to the doctorate. It brings together a set of research units grouped around a given scientific field. The doctoral school is responsible for recruiting, monitoring, training and defending doctoral candidates. It offers courses and scientific activities to doctoral candidates and validates each doctoral candidate's individual educational plan.
The main doctoral schools in AI can be found at the following link. Each doctoral school organizes a call for applications, typically open in spring of each year. Further details can be found on their respective websites.
The call for doctoral projects within the Sorbonne University Alliance is launched every year at the end of January. The call for doctoral applications is generally open until March and interviews take place in May.
A detailed calendar is posted each year in the News section of the website.
The Cifre (Industrial agreement of training through research) system allows French companies, local authorities or associations to entrust a doctoral candidate with an assignment in the framework of a research collaboration with an academic research laboratory affiliated to a doctoral school. An important benefit is that the fellow works in the company as well as the laboratory, thereby gaining valuable experience in both worlds and understanding their different research aims and approaches.
Professional training is at the heart of the national AI strategy, with the goal to educate AI talent at all levels. It is therefore necessary to propose new options and new formats for continuing education in connection with changes in usage but also through concrete experiments and articulated with actions aimed at certain categories of professionals. In this frame, SCAI supports multiple efforts in continuing education, such as:
AlphaZero, which beats the best players in the world at Go, the OpenAI robot that manipulates a cube from all sides or solves the Rubik's cube, a group of agents that beats professional players at StartCraft or Dota2, an algorithm that reduces the cooling bill of Google's computer centres by 40%, all of which are high-profile successes of reinforcement learning that have made it a major component of artificial intelligence.
This training will give you the basics to understand reinforcement learning and will guide you towards the implementation of the most commonly used algorithms in the field.
Every Thursday from 20 May 2021 to 17 June 2021 inclusive (5 Thursdays), from 9 am to 6 pm (35 hours).
The objective of this training is to complement and enrich the skills of professionals in the areas of data analysis and information technologies in the following fields:
This training takes place 2 days/month (Friday and Saturday), from October to April.
Sorbonne University Continuing Education and Ecole polytechnique Executive Education have joined their expertise in Science to offer the Financial Engineering Degree for executives, which is the Executive version of the famous Parisian degree in financial mathematics.
Taught by an educational team from the leading French universities, this program is focused on acquiring, completing and updating professional skills knowledge in Mathematical, statistical and numerical methods for financial markets, accounting for the recent developments of data science and artificial intelligence contributions.
The training takes place 2 days/month (Friday and Saturday), from October to May.
This short training identifies the opportunities of deep learning to meet business needs, as well as to add value in professional projects using deep learning.
The training offers the basics and the good practices of machine learning: to understand the general principles of a neural network, to understand the types of neural architectures and to know how to select them to treat a specific problem. The course also teaches visualization and interpretation of the results provided by a neural network.
The training takes place over 3 consecutive days, usually in June.
Launched in 2020 and based in Sorbonne University Abu Dhabi, this high-level training in Machine Learning and Artificial Intelligence, taught in English, offers a uniquely devised blend of lectures and practical classes, specifically tailored to the needs of the twenty-first century professional.
By acquiring honed competencies in the models and the tools of machine learning and big data, trainees are able to bring about critical innovation in technological, innovation-thirsty societies. Moreover, she/he will develop a mature understanding of the opportunities and challenges posed by a large-scale use of artificial intelligence devices (such as text mining, analysis of complex networks, image processing and online advertising etc.).
The training consists of three 30-hour Teaching Modules, each spanning a full week. Modules are scheduled once a month for three consecutive months.
SCAI also offers tailor-made professional training at the request of companies or public and private organizations.
Do not hesitate to contact us to discuss your needs and expectations.