D&K : Data & Knowledge

Dernière mise à jour : 
Dec 1, 2015
Master II
Scolarité : 
 € par an
The Data & Knowledge program is a second year master program (“M2”) in computer science at the University Paris-Saclay in Paris, France. It is concerned with Web data management, knowledge & semantics, big data, and data analytics from a semantic point of view.

The curriculum brings together a variety of subjects from the fields of data management, knowledge management and knowledge engineering, and machine learning, and data mining. Topics include system design and architecture, storage, indexing and optimization, data analytics, knowledge representation and reasoning, semantic interoperability, and data mining, all with a special focus on processing very large amounts of data.

The unique combination of these disciplines distinguishes us from the other M2 tracks that focus either on data management or machine learning and data mining. Another key feature is that the Data&Knowledge track will be in English.

The program will allow you to

  • look under the hood of technologies that big data players such as Google, Twitter, and Facebook leverage
  • learn the principles of semantic data representation, which makes machines “understand” data
  • understand how machines (and humans) reason on data
  • discover different types of data in a variety of applications, such as bioinformatics, social media, and the Web

Research : The combination of big data and semantics in all of its forms is an active field of research. Students will be prepared for research in Web technologies, the Social Web, Data Analytics, Big Data Management, Knowledge Base Management, Information Extraction, Information Retrieval, Databases, Data Warehousing, Knowledge Representation, and Distributed Data Management.

Professional careers : The Data&Knowledge track will prepare students for careers as information management professionals or data-savvy IT generalists. Targeted job profiles are software engineer, data scientist,software and system architect, quality engineer, project manager, or engineer.

S3 - Semestre 3

Mandatory courses

Complex Data and Knowledge

Architectures for Massive Data Management

Data Warehousing

6 optional courses

Reasoning with Ontologies

Knowledge Base Construction

Cognitive Modeling

Information Integration

Social Data Management

Uncertain Data Management

Dynamic Content Management

Distributed Data Mining and Machine Learning

Data Science for Big data

Learning from the Web

Very Large Data and Knowledge in Bioinformatics

New trends in Data&Knowledge

S4 - Semestre 4


Formation à la recherche / à l'entreprise

Six months master thesis project

Lieux d'enseignement