Paris-Saclay Data Science Master
The two-year master allows students to gain the necessary skills for handling today’s massive amount of data, characterized by its 4 V’s: volume, velocity, variety and veracity. The curricula contains courses along 3 axis : 1) massive data management, both theoretically (principle of DBMS, NoSQL and graph databases) and applied, 2) artificial intellligence, both symbolic and numerical (machine learning), and 3) data mining and knowledge management. Theoretical bases are complemented by applied projects and research or industrial internships.
To validate the master, students need to validate 120 ECTS, in a combination of mandatory classes, optional classes, soft skills classes, and projects/internships.
Coursers are organized in periods each consisting of 6 weeks of classes and one for exams:
- M1 - 4 periods of classes: P1 (sep-oct), P2 (nov-dec), P3 (jan-feb), P4 (mar-avr)
- M2 - 3 periods of classes: P1 (sep-oct), P2 (nov-dec), P3 (jan-feb) plus a long internship
For optional classes, students can choose any open course from the other master in the computer science department, with the restriction that in M1 there should be no more than 4 classes per period (mandatory+optional), and in the M2 no more than 3 classes. The full list can be found [here].
Exceptionally, students admitted directly in the second year can choose first-year mandatory Data Science classes as their optionals.
In the first year (M1), the following mandatory courses need to be validated:
[DS] Bases de données avancées I : Optimisation (P1)
- [DS] Bases de données avancées II : Transactions (P2)
[AI] Foundational Principles of Machine Learning (P2)
- [DS] Intelligence Artificielle, Logique et Contraintes I (P3)
[DS] Distributed Systems for Massive Data Management (P3)
- [DS] Intelligence Artificielle, Logique et Contraintes II (P4)
- [AI] Large-Scale Distributed Data Processing (P4)
In the second year (M2), the following mandatory courses need to be validated:
- [DS] Algorithms for Data Science (P1)
[DS] Semantic Web and Ontologies (P1)
- [DS] Social and Graph Data Management (P2)
- [DS] Knowledge Discovery from Graph Data (P2)
[AI] Optimization (P2)
- [DS] Web of Data (P3)
- [HCI] Interactive Information Visualization (P3)
First classes week of September 6th, 2021 with orientation on September 3rd, 2021.
The schedule of the track and the master in general can be found [here]
[Silviu Maniu] (first year, overall)
[Fatiha Saïs] (second year, internships)
[Alexandre Verrecchia] (administrative issues)
Master Presentation (French) [pdf]
Other Links [Computer Science Master] (French)