Education
Published on November 26, 2018 | Updated on June 25, 2019

International master's in machine learning and data mining - MLDM

HARD SCIENCES / DATA SCIENCE SPECIALISTS

© Droits réservés

© Droits réservés

The Master's in Machine Learning and Data Mining (MLDM) is an international Master's program taught entirely in English, which trains specialists over two years in machine learning and data mining. It prepares students for an academic career or an activity in the R&D centers of large groups that require expertise in data science.

CURRICULUM

Students in the MLDM program will earn 120 ECTS over a twoyear period, divided into four semesters. It provides students with the opportunity to complete two internships in research laboratories or companies: one internship of at least 3 months during the first year, and an internship of at least 4 months during the second year (master's thesis). Students may spend the third semester abroad, thanks to selected partnerships with the KU Leuven (Belgium), Leiden (Netherlands), Freiburg (Germany), Turin (Italy), Vienna (Austria). As such, the MLDM program has an original scientific position at European level to deal with issues related to decision-making support, data mining, big data, modeling, classification, etc. The MLDM program is supported by a team of professors from the Hubert Curien Laboratory – UMR CNRS 5516 of international renown in the field of Machine Learning et Data Mining.


PREREQUISITES FOR ADMISSION

Admission based on academic transcripts following a Bachelor of Science (or equivalent degree) in Computer Science, Mathematics or Statistics.


LIST OF TEACHING UNITS

First semester (30 ECTS)

• Advanced Algorithmics
• Calculability and Complexity Theory
• Introduction to Machine Learning
• Data Analysis
• Research Methodology
• Introduction to Artificial Intelligence
• Foreign Language


Second semester (30 ECTS)

• Data Mining and Knowledge Discovery
• Machine Learning - Fundamentals and Algorithms
• Computer Vision
• Computer Networks and Security
• Optimization & Operational Research
• End of year project/Internship


Third semester (30 ECTS)

• Advanced Machine Learning
• Data Mining for Big Data
• Deep Learning and Applications
• Machine Learning and Data Mining Project
• Semantic Web
• Multi Agent Systems


Fourth semester (30 ECTS)

• Master Thesis - Internship from early February to late June