Courses of the second year of the EIT Data Science curriculum

  1. First semester courses
  2. Second semester courses

First semester courses

Scientific and technical courses

  • Machine Learning II (5 ECTS)

    • Classification
    • Ensemble Learning
    • Regularization
    • Lecturer: Simon Malinowski
  • Symbolic Data Mining (5 ECTS)
    • Data pre-processing
    • Association rules
    • Clustering
    • Concept learning, version space
    • Lecturer: Sébastien Ferré
  • Indexing and Visualization (4 ECTS)
    • Tools to analyse and index text documents
    • Feature extraction for image representation
    • Visualization tools for structured data
    • Lecturer: Ewa Kijak, Vincent Claveau
  • Data Warehouses (3 ECTS)
    • Lecturer: Marc Bousse
  • Cloud and Big Data Management (3 ECTS)
    • Lecturer: Gabriel Antoniu
  • Case Study in Data Science (5 ECTS)

Innovation and entrepreneurship courses

  • IES: Innovation & Entrepreneurship Study (6ECTS)
Test your knowledge and skills. In this module, you will have to demonstrate your ability to applying, synthesizing, and evaluating prior Innovation and Entrepreneurship learning in a specific innovation and/or entrepreneurial management context. You will have to know about the state of the art of a particular innovation, be aware of the skills needed in a certain innovation or entrepreneurial management process, and be able to critically discuss the applicability of a set of innovation techniques in the setting of a real innovation project.

Second semester courses

  • Internship/Master Thesis (30 ECTS)