Artificial intelligence and decision specialization (M2), M.Sc.

  • Application Deadline
  • 12 months
  • Tuition
  • French
University rank #39 ,
The "Artificial Intelligence and Decision (IAD)" specialization provides theoretical and practical tuition and covers the main fields of artificial intelligence and decision-making, in particular: adaptive agents and decision-making agents, learning and data mining, optimization and resolution of problems, intelligent data bases, multimedia information processing, man/machine interaction.
  • Overview
  • Programme outline
  • Key facts
  • Admission requirements
  • Fees and funding


The "Artificial Intelligence and Decision (IAD)" specialization provides theoretical and practical tuition and covers the main fields of artificial intelligence and decision-making, in particular:

  • adaptive agents and decision-making agents
  • learning and data mining
  • optimization and resolution of problems
  • intelligent data bases
  • multimedia information processing
  • man/machine interaction

The IAD specialization works in close cooperation with several grandes écoles (Telecom ParisTechn, ENSTA and ensIIE) and associates them in its tuition. It uses a strong research base, firstly at UPMC with the Computing Laboratory of the Pierre and Marie Curie University (LIP6) of which two of the five research departments (the DAPA: Data and automatic learning and DESIR: Decision, Intelligent Systems and Operational Research departments) are entirely dedicated to the "Artificial Intelligence and Decision" field and ISIR for interactions between "robotics and artificial intelligence"; the IAD specialization also uses other laboratories in partner schools and in particular the Ecole Nationale Supérieure des Télécommunications' Information Processing and Communication Laboratory (LTCI) (Telecom ParisTech), and the Conservatoire National des Arts et Métiers' (CNAM) Computing Research Centre (CEDRIC). Its purpose is to train SICT (Sciences and Information and Communication Technologies), perfecting their knowledge of the concepts, models and tools of artificial intelligence, decision-making and operational research.


the IAD specialization covers highly practical and current issues such as those dealing with:

  • information and decision systems,
  • web data bases,
  • multi-agent systems,
  • data mining and access through content to multimedia documents,
  • interactive television,
  • production engineering,

which ensure professional openings for this specialization. It also tackles more theoretical fields used in cutting-edge research in our laboratories such as:

  • logic modeling
  • decision theory
  • symbolic and numeric learning,
  • adaptive agents,
  • modeling of complex systems,
  • discrete or continuous optimization,
  • operational research.
This pioneering course, taught by recognized experts, assures the training of future specialists, engineering and researchers alike, in a rapidly expanding field.

Programme Structure

All the first year papers are worth 6 ECTS, including a substantial team project. The second year papers are all worth 3 ECTS, except for the end of year internship, which is worth 18 ECTS. The internship takes place either in a laboratory or in a company, and lasts a minimum of five months.

All the major´s specializations have both a research and a professional orientation. At the beginning of the course, students choose the specialization that will define the set of fundamental and technological knowledge that they wish to learn. There are set programs defined within each specialization to help students make their choice according to their personal and professional objectives.

The Computer Science major has been organized to promote double majors with mathematics, electronics and acoustics.

Specializations offered in M2:

  • Electronic systems, computer systems (ex ACSI)
    The specialization trains specialists in the design of circuits and integrated electronic systems, which are at the heart of most industrial equipment (automobile, telecommunications, gaming, whiteware, etc...).
  • Artificial intelligence and decision (in French, IAD)
    The IAD specialization trains information technology specialists who master the concepts, models and tools of artificial intelligence, decision support systems and operations research.
  • Imaging (IMA)
    The imaging specialization gives students advanced training in fields linked with imaging. It includes coherent programs ranging from the foundations of the discipline to the most advanced techniques.
  • Networks
    The networks specialization trains researchers in fields such as network design and telecommunications systems, transmission of media streams and the internet of the future. It also qualifies "generalist" network engineers, telecommunications systems developers and network and systems administrators.
  • Distributed systems and applications (in French, SAR)
    The SAR specialization trains specialists in design and development of distributed systems, capable of understanding and implementing the methods, techniques and mechanisms of the discipline.
  • Science and technology of software (in French, STL)
    The STL specialization trains specialists in development and monitoring of software applications, with a solid foundation in programming languages and algorithmic techniques.
  • Bioinformatics and modeling

Detailed Programme Facts

  • Full-time duration 12 months
  • Study intensity Full-time
  • Languages
    • French
  • Delivery mode
    On Campus
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Academic Requirements

This specialization is for scientific students with good computer science and/or computer science-applied mathematics knowledge. The first year group is mainly made up of students with a bachelor's degree in computer science or mathematics (with credits in programming and algorithms), but other less typical paths are also considered attentively. Second year students are made up in part with students from the first year and in part from student engineers, in particular from the schools associated with our specialization.

The course prerequisites are firstly a general computer science diploma including good skills in algorithmics and programming (e.g. Java or C++) and secondly a good level of basic mathematics (logic, algebra, analysis, probability etc).

Tuition Fee


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