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.

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.

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.

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.

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 for infrastructure management
• 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.