Data & Knowledge
⚠️ Attention : cette formation ne semble actuellement plus dispensée ⚠️
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 program is held in English (even if the "programmes" on the left say otherwise).
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 is 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
The Data&Knowledge track will prepare students for careers as information management professionals or data-savvy IT generalists, or for research in areas related to discovery and management of very large data and knowledge. Potential carreers include : IT executives in businesses, careers in research and development in universities and private research, IT careers in large companies and start-ups. Targeted job profiles are Software Engineer, Data Scientists, Data Analysts, Data Engineers, Software and System Architects, Quality Engineers, Project Managers, Engineers, or Researchers.
Semestre 3
Mandatory courses
Web Data Models
Data Warehousing
Machine Learning and Data Mining
Big Data Processing
Novel Architectures for Big Data Analytics
6 optional courses
Knowledge Base Construction
Natural and Artificial Intelligence
Information Integration
Social and Uncertain Data Management
Dynamic Content Management
Data Mining Theory and Practice
Managing Very Large Data and Knowledge in Bioinformatics
IoT Big Data Stream Mining
New trends in Data&Knowledge
S4 - Semestre 4
Softskills Seminar
Introduction to Research and Business
6 month master thesis project