Science, Engineering

Artificial Intelligence and Data Science

  • ECTS

    120 credits

  • Duration

    2 years

  • Training Structure

    College of Sciences

  • Language(s) of Instruction

    French

Overview

This Artificial Intelligence and Data Science track trains specialists with advanced skills in programming, the design and development of intelligent information systems, and automated data analysis. The program comprises four closely related areas:
1) learning, extraction, or acquisition of data (machine learning)
2) automatic data analysis, particularly of textual data, i.e., natural language processing (NLP)
3) the representation and storage of data and their semantics
4) data processing and reasoning based on semantic knowledge, for example, for decision support.
Programming these methods is covered in every course as well as in the software engineering courses within the program.

Students who have completed a CMI-accredited (Master’s in Engineering)computer science bachelor’s degree may continue their studies in the CMI program in the following tracks: Algorithms (Algo), Software Engineering (GL), Imagine (Imagine), and Artificial Intelligence and Data Science (IASD). As a reminder, the Master of Engineering in Computer Science is a rigorous, intensive five-year program that builds upon the Bachelor’s–Master’s degree track in Computer Science by adding specific course units. The CMI was developed as a complementary training model for engineering professions, consisting of a five-year degree program leading to a Master’s in Engineering, corresponding to the international Master of Engineering model. This CMI designation guarantees a coherent and rigorous university curriculum preparing students for careers as expert engineers. Upon completion of the CMI in Computer Science, graduates receive—in addition to the Master’s in Computer Science—a Master’s in Management from the Institute of Business Administration (IAE), the Figure network accreditation, and a university diploma (D.U.) in the Master’s in Engineering—Computer Science program. The CMI in Computer Science is offered as a work-study Master’s 2 program.

For students interested in earning a dual degree from the IAE—a Master’s in Technology and Science Management: the option is available (based on application review) to pursue, concurrently with the initial program, a management program leading to a Master’s degree in Technology and Science Management. Over the course of the two-year program, the curriculum alternates between computer science courses (taught by the FdS) and management courses (taught by the IAE), with a joint internship approved by both institutions in the second year. This dual-degree program allows students to graduate with both a Master’s in Computer Science and a Master’s in Management of Technology and Science.

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Objectives

The goal of this program is to train high-level IT experts and executives in programming, in the fields of artificial intelligence and data science, who are proficient in both statistical and formal methods. Graduates of the Master’s in Computer Science with a specialization in Artificial Intelligence and Data Science are capable of designing and developing software for the automatic analysis of large datasets—particularly textual ones—as well as algorithms for automatic data acquisition and the representation of their semantics; they are also capable of programming methods and algorithms for Big Data, Machine Learning, and Artificial Intelligence; they are also able to model and automate reasoning about data and its semantics.

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Expertise and Skills

The program provides a balanced mix of theoretical and conceptual foundations and hands-on programming training in the latest technologies, enabling both rapid entry into the workforce and the scientific perspective necessary to adapt to future developments in computer science. The curriculum enables students to master and apply the methods and tools of language, data, and knowledge engineering—including artificial intelligence, machine learning, and data management—while strengthening their programming skills and their proficiency in information systems and web technologies.

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Organization

Knowledge Assessment

https://mcc.umontpellier.fr/ listsall course units (UE) and their assessment methods.

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Open on an alternating basis

Contract Type

Apprenticeship Contract, Professional Training Contract

The second year (M2) can be completed as a work-study program through professional training or apprenticeship contracts. Work-study students become employees for the duration of their M2 (typically under a contract running from September 1 to August 31). The academic year is structured as follows: during the university lecture/tutorial/lab period, the work-study student is on campus to attend classes; during university breaks and internship periods, the work-study student is at the company (1 week in November, 2 weeks in December, and from the last week of January through August 31; this amounts to 8 months out of 12 spent at the company).

It is important to note that a professional training or apprenticeship contract is a tripartite agreement between the student, the company, and the university: the approval of the program director is required; their decision is based on the student’s academic performance in the first year of the master’s program (M1) and on the recommendations of the track coordinators. Therefore, excellent academic performance in the M1 is expected in order to receive approval for the work-study program.

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Program

Select a program

  • English S1

    2 credits
  • Probability, Statistics

    2 credits
  • Foundations of Symbolic AI

    4 credits
  • CHOICE 1

    4 credits
    • Choose 1 of 4

      • Distributed Software Architectures

        4 credits
      • Cryptographic Foundations for Security

        4 credits
      • POA/SMA

        4 credits
      • Graphs: Structures and Algorithms

        4 credits
  • Algebra, geometry, transformation, numerical computation

    2 credits
  • Logic, Computability, and Complexity

    4 credits
  • Software Engineering

    4 credits
  • Distributed Programming

    4 credits
  • Data Warehouses and Big Data

  • Machine Learning 1 (Traditional Methods)

    4 credits
  • T.E.R.

    4 credits
  • English S2

    2 credits
  • Semantic Data Processing

    4 credits
  • Logic for Software Engineering and AI

    4 credits
  • Mobile Development and Programming

    4 credits
  • Natural Language 1 (Syntax)

    4 credits
  • OPTION 2

    4 credits
    • Choose one of the following two options:

      • Epistemology of Computer Science

        4 credits
      • Project Management

        4 credits
  • Natural Language 2 (Word and Sentence Semantics)

    4 credits
  • Decision Support

    4 credits
  • Machine Learning 2 (Advanced Methods)

    4 credits
  • Database Theory and Knowledge

    4 credits
  • Conferences

    2 credits
  • Data Management Beyond SQL (NoSQL)

    4 credits
  • CHOICE 1

    8 credits
    • Choose 2 out of 3

      • Database Administration

        4 credits
      • Advanced Mobile Development, IoT, and Embedded Systems

        4 credits
      • Constraints

        4 credits
  • OPTION 2

    30 credits
    • Choose one of the following two options:

      • Industrial Internship

        30 credits
      • Academic Internship

        30 credits

Admission

Admission Requirements

Admission to the master's program is based on application review for holders of a bachelor's degree in computer science (or equivalent).

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Registration Procedures

Applications can be submitted through the following platforms: 

French and European students:

International students from outside the EU: Follow the “Études en France” procedure for the M2 program: https://pastel.diplomatie.gouv.fr/etudesenfrance/dyn/public/authentification/login.html

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Capacity

And then

Continuing Education

Doctorate (by competitive examination).

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Employment Placement

Business Sectors:All fields related to artificial intelligence, machine learning, data science (Big Data), or natural language processing—that is, those involving the management, use, and computer-based processing of documents and data.

Job Types:Data Scientist (Big Data Engineer), NLP Engineer/Scientist, AI Engineer/Researcher, ML Engineer, ML Expert, Knowledge Engineer

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