News: Applications are closed. We no longer accept applications.
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, artificial intelligence, and data analytics from a semantic point of view. The program is taught in English.
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 reason on data
- discover different types of data in a variety of applications, such as bioinformatics, social media, and the Web
The rise of user-web interaction and networking, coupled with technological advances in processing power and storage capability, has led to a growing demand for effective and sophisticated techniques for discovering and managing knowledge, in particular in connection with the new rise of Artificial Intelligence. Businesses need to transform large quantities of raw data into knowledge, and they rely on modern database and knowledge management systems to make informed and often business-critical decisions. Similarly, scientists have to process massive amounts of data to gain new insights and advance reseach.
The master program will equip students with the fundamental knowledge, technical skills and concrete applied methodologies for exploiting and making sense of large real-world data sets, which are typically very large and may consist of multiple heterogeneous databases and knowledge bases. In particular, students will acquire experience in using and developing data-supported smart services and tools for data-driven decision making and will learn how to master technical and scientific challenges in processing large data and knowledge. The program 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.
"Big Data" has become a buzz word in recent times. Candidates are advised that actually studying the science and technology behind Big Data is an endeavor that is more arduous than the buzz word suggests. It involves learning the theoretical background, the tools, and the algorithms that are used to treat large data volumes. In return, students will be prepared for the professional or academic future even when the hype around Big Data ceases one day.
The Data & Knowledge program also teaches the basics of machine learning, but this is not the main focus of the program. Students who wish to deepen their knowledge in machine learning can use the "Module Liberté" to this end. The Module Liberté is an optional course that can be chosen among all data-oriented courses offered at Paris-Saclay -- for example a course from the machine learning program. The Module Liberté is a particular advantage of the Data & Knowledge program; other programs usually do not allow this flexibility.
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, software and system architects, quality engineers, project managers, engineers, or researcher.
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.
Students who wish to pursue a PhD afterwards are more than encouraged to do that. The Paris Saclay University and the associated research labs (INRIA, CNRS, etc.) offer a great environment for a PhD, and our program is an optimal preparation for this path.
The Data&Knowledge program is an international program that is held in English. It explicitly welcomes foreign applicants. Developing language skills will be an integral part of the mandatory soft-skills course. The program is taught in English.
Modalités de contrôle des connaissances associées aux unités d'enseignement des S1 et S2
Accédez au détail des répartitions horaires Cours/TP/TD
- S3 - Semestre 3
Matières Ects Cours TD TP Web Data Models 2.5 - - - Semantic Web 2.5 - - - Data Warehousing 2.5 21h 15h 6h Machine Learning and Data Mining 2.5 - - - IoT Big Data Processing 2.5 - - - Novel Architectures for Big Data Analytics 2.5 - - -
6 optional courses
Matières Ects Cours TD TP Knowledge Base Construction 2.5 15h - 6h Natural and Artificial Intelligence 2.5 - - - Information Integration 2.5 12h 9h - Social and Uncertain Data Management 2.5 15h - 6h Dynamic Content Management 2.5 15h - 6h Data Mining Theory and Practice 2.5 15h - 6h Managing Very Large Data and Knowledge in Bioinformatics 2.5 9h 6h 6h IoT Big Data Stream Mining 2.5 - - - New trends in Data&Knowledge 2.5 14h 4h 3h
- Mandatory courses
- S4 - Semestre 4
Matières Ects Cours TD TP Softskills Seminar 2.5 3h 9h 9h Introduction to Research and Business 2.5 6h 6h 9h 6 month master thesis project 25 - - -
First semester, first period
We follow the shared calendar of Paris-Saclay. The first period runs 09/09/2019 - 28/10/2018, with 7 weeks of classes, and the exams in the weeks of 04/11/2019 and 11/11/2019. The calendar and the rooms for the first period will be available in Synapses. Details for all courses are in the examination modalities. The morning slot is 9:00-12:15, the afternoon slot is 13:30-16:45.
We will try to liberate September 12th and 13th for the Junior Conference on Data Science and Engineering.
The mandatory courses are:
- DK910a: Web Data Models (Nicole Bidoit) - Monday morning (PSud, PUIO building, normally room E210)
- DK908b: Big Data Architectures (Ioana Manolescu) - Monday afternoon (PSud, PUIO building, normally room E210)
- DK911a: Data Warehouses (Benoit Groz) - Tuesday morning (PSud, PUIO building, normally room E212)
- DK910b: Semantic Web (Yue Ma) - Tuesday afternoon (PSud, PUIO building, normally room E210)
- DK911b: Machine Learning (Filippo Miatto) - Wednesday morning (Télécom, nornally Amphi Jade)
- DK908a: Big Data Processing (Louis Jachiet) - Wednesday afternoon (Télécom, nornally Amphi Jade)
- DK915: Introduction to Research and Business (Emmanuel Waller, Fabian Suchanek, Vera Dickman) - Thursday morning (no course on September 12th, but an additional session on September 19th afternoon) (PSud, PUIO building, normally room E105)
First semester, second period
The second period runs 18/11/2019 - 13/01/2020, with 7 weeks of classes, and the exams in the weeks of 27/01/2020 and 03/02/2020. Details for all courses are in the examination modalities.
- DK907: Softskills seminar (Fabian Suchanek & all lecturers) - Thursday afternoon (Télécom ParisTech)
Optional courses: 6 out of the following
- DK914: Information Integration (Nathalie Pernelle, Fatiha Saïs & Sarah Cohen) - Monday afternoon (UPSud)
- DK917: Factorization-Based Data Analysis (Umut Simsekli) - Tuesday afternoon (Telecom ParisTech)
- DK904: Data Stream Mining (Albert Bifet, Jesse Read) - Wednesday morning (Telecom ParisTech)
- DK906: New Data on the Web (Fabian Suchanek, Nicoleta Preda) - Wednesday afternoon (Telecom ParisTech)
- AIC-D-K922: Image understanding (Isabelle Bloch) - Friday morning (Orsay)
- AIC-D-K921: Image mining and content-based retrieval (Antoine Manzanera) - Friday afternoon (Orsay)
- two DK916x: Module Liberté (any data-oriented course at UPSay by approval)
6 month master thesis project: 25 ECTS
6 month industrial internship: 25 ECTS
See our internship regulation.
*** Applications are closed. We no longer accept applications. For the programs next year, check again in December 2019. ***
We cannot support Eiffel scholarships unfortunately. You cannot apply for an Eiffel scholarship with us...
- Applicants must have finished 4 years of study (BAC+4) in Computer Science (or equivalent), either at Paris Saclay University or elsewhere.
- Applicants should have good programming skills in Java.
- It is not possible to do the program part-time ("en alternance")
- The tuition fee will not exceed 400 € (four hundred euros) per year, i.e., for the entire program.
- Check whether you have to apply also via Campus France.
During the application process
- Application for both the program and the scholarship works exclusively via the Apply button on the left. Please refrain from sending your CV or any other material by mail unless requested!
- We insist on a motivation letter in English. This means that the motivation letter is not in French. Also, please make sure your CV mentions clearly the country and the full name of the university where you graduated.
- If you cannot upload a document that the system considers obligatory, create a PDF document in which you explain the reason, and upload this document instead. You can produce a PDF document, e.g., with Microsoft Word.
- For problems with submitting your application (obligatory fields missing, alleged incoherences, information missing, etc.): try to fill out the fields in such a way that the tool accepts your application. The applications are anyway read by humans afterwards.
- It’s OK if you have not yet finished your current program. Just send the transcript of grades until the current state of your studies.
- Documents can be in English or French (but the motivation letter has to be in English).
- The final obligatory document that the system asks for is the list of all your university grades
- A certificate for French language capabilities is not required.
- A certificate for English language capabilities is required. If you have studied in English, submit a PDF file that proves (or at least states) this fact.
Scholarships (DigiCosme and Paris-Saclay)
- If you wish to be considered for a scholarship, please let us know in your motivation letter.
- No separate process (and no email) is needed to be considered, just state in your motivation letter that you wish to be considered.
- Apply as early as possible (April 1st)
- Scholarships will be awarded based on merit, and we only have 1-3 per year.
- You will receive a notification of acceptance or rejection within 2 months the latest by email. Usually, you will get a reply within 4 weeks. Please refrain from inquiring about the status of your application.
- Applicants will be informed about the acceptance or rejection by email.
- Applicants who qualify for a scholarship will be informed about the scholarship at the same time. Thus, if you are accepted to Data&Knowledge, but did not receive any separate mail about the scholarship, it means that you have not been selected for the scholarship.
- The application process is very competitive: We receive around 400 applications, and have only around 30 students in the end.
- The acceptance email serves as proof of acceptance. You can receive a written letter of acceptance upon request.
- The acceptance email reads "pending validation of the required conditions". This means that we expect that you finish the degrees that you indicated in your application for the current year.
- Please read our document about the registration process.
EIT Digital Master School
The M2 Data&Knowledge can be followed as part of the 2 year EIT digital Master School program at Paris-Sud University. To apply for this avenue click here. Applications for the entire EIT Digital Master School (M1+M2) can only be handled at the EIT website.
You find here the regulations that govern our program:
- registration procedure for newly accepted students
- study regulations (grades, internship, etc.)
- internship regulation
- examination modalities for each course
The program is run by Paris-Sud University and Télécom ParisTech University. The reference institute is Télécom ParisTech University.
The Data & Knowledge program is an international program that is held in English. It explicitly welcomes foreign applicants. Developing language skills will be an integral part of the mandatory soft-skills course. Presentations and reports will be given by students in English.
This program is part of the Cloud Computing and Services major (CCS) of the EIT Digital Master School, offered via Université Paris-Sud (https://masterschool.eitdigital.eu/programmes/ccs/).
Les modalités d'examen de la candidature sont les suivantes : Examen de dossier à déposer sur le site web de l'UPSaclay
Pièces justificatives obligatoires
Pièces justificatives facultatives
Il est rappelé aux personnes en situation d'emploi qui souhaitent demander une valorisation des Acquis Professionnels et Personnels qu'elles doivent déposer un dossier accessible à l'adresse suivante : https://www.universite-paris-saclay.fr/fr/etre-candidat-a-nos-formations