• The program is structured into two complementary semesters allowing students to acquire fundamentals and then specialize.

    Fall Semester

    The fall semester establishes essential foundations through three fundamental courses:

    • Data and Digital Society to understand the economic, legal, and ethical implications of data
    • Applied Statistics to master mathematical foundations
    • Fundamentals of Machine Learning to grasp key concepts of machine learning

    This foundation is complemented by a choice of computer science courses:

    • Data Science Toolkit and Applications is mandatory for students who need to strengthen their programming skills
    • Introduction to Big Data and Spark or Advanced C++ Programming are offered to more advanced students

    The semester concludes with Advanced Machine Learning, allowing students to deepen their understanding of the most recent artificial intelligence techniques.

    Fall Semester Data Science TAF

    Spring Semester

    The three major career paths (Data Science & Machine Learning, Data & Analytics, Data Engineering & Architecture) are divided into four tracks in spring, offering a more refined vision and skill combinations adapted to different business needs.

    Spring Semester

     

    Data Science - Real World Applications (24 spots)

    This track emphasizes practical implementation through:

    • A Journey to Data Scientist, which guides students through a complete data project
    • Prototyping of Data Mining Workflow which enables mastery of the CRISP-DM methodology

    This hands-on approach is ideal for future Data Scientists and Machine Learning Engineers.

    Access Conditions
    • Have completed the core courses of the specialization: "Data and Digital Society", "Applied Statistics", "Fundamentals of Machine Learning" and "Data Science Toolkit and Applications"
    • Alternatively, be able to demonstrate acquisition of the following competencies:
      • [BC-02] Effectively communicate insights derived from data through visualization and statistical analysis
      • [BC-07] Design and implement end-to-end data science projects using industry-standard tools and libraries
      • [BC-04] Implement and evaluate machine learning algorithms on real-world datasets

     

    Data Science - Manage Data Variety (30 spots)

    This track explores cutting-edge domains with:

    • Heterogeneous Data & Knowledge Processing for managing data diversity
    • Natural Language Processing and Text Mining for automated language processing
    • Graph Theory & Social Networks Analysis for network analysis

    These skills are particularly sought after for advanced artificial intelligence projects.

    Access Conditions
    • Have completed the core courses of the specialization: "Data and Digital Society", "Applied Statistics", "Fundamentals of Machine Learning" and "Data Science Toolkit and Applications"
    • Alternatively, be able to demonstrate acquisition of the following competencies:
      • [BC-02] Effectively communicate insights derived from data through visualization and statistical analysis
      • [BC-07] Design and implement end-to-end data science projects using industry-standard tools and libraries
      • [BC-04] Implement and evaluate machine learning algorithms on real-world datasets

     

    Decision Science (40 spots)

    This track trains students in decision-making with:

    • Combinatorial Optimization for solving complex optimization problems
    • Multi-criteria Decision Aiding for supporting strategic choices

    This specialization meets the needs of future Data Analysts and Decision Support Analysts who will need to transform data into decisions.

    This pathway is accessible to all students who have completed the first year of the engineering cycle at IMT Atlantique or equivalent training.

    Data Engineering (24 spots)

    This track develops technical skills with:

    • Data Engineering Foundations for mastering databases and data pipelines.
    • Advanced Big Data Architecture for massive data processing
    • Business Intelligence for creating decision-making dashboards

    These skills are essential for Data Engineers and Big Data Architects who build the foundations of modern information systems.

    This pathway is accessible to all students who have completed the first year of the engineering cycle at IMT Atlantique or equivalent training.