For this interational track, specific fees are applied.
Historically, business intelligence has been the combination of techniques linked to data storage and mining. However, we can now expect major changes in business intelligence software and the emergence of important new research and innovations in this field. This is because the data being handled is changing (whether it is structured in databases or unstructured, for example in documents), users are changing (with fewer IT specialists) as are communication methods (smartphones, tablets, social media).
This Master’s program aims to provide the key elements required to meet these challenges in terms of semantic technologies, analytic visualization, decision science and data mining.
- S3 - Semestre 3
Matières Ects Cours TD TP Data Mining and Machine Learning 5 24h - 24h Corporate Semantics and Semantic Web 5 24h - 24h Visual Analytics 5 24h - 24h Decision Modelling 5 24h - 24h Introduction to Innovation and Research 5 12h - 18h Humanities 5 - - 60h
- S4 - Semestre 4
Matières Ects Cours TD TP Master's Thesis 30 - - -
Demand for data scientists will be high in the coming decade: data science has key applications for private individuals (information search, education, culture, social media), in science (e-science) in the social sector (healthcare, education, e-government) and in the business world (industrial production, advertising, trade). The success and relevance of these applications depend on the development of innovative methods that are able to process heterogeneous, distributed and very large datasets (big data).
Career opportunities for students in this field include executive IT positions in industry or the services sector, or data management research and development positions in universities or public and private research organizations, or in major groups and startups. More specifically, career opportunities following the DSBI track include those linked to the models and technologies of decision support systems research and development. The program is underpinned by the Erasmus Mundus IT4B1 (Information Technologies for Business Intelligence) Master’s program.
More than 20 laboratories and research units contribute to the Université Paris-Saclay Computer Science Master’s program, providing an ideal environment for students who are considering a doctorate afterwards. These teams are working towards realizing the promises of the digital revolution and developing the tools that will become the technologies of the future.
Social and economic partners
The Computer Science Master’s program created within Université Paris-Saclay benefits from an exceptional location inside an ecosystem that brings together a large number of economic players in the ICT sector. Master’s students will benefit from the University’s proximity to the Systematic and Cap Digital competitiveness clusters, innovation organizations (IRT SystemX, lncuballiance) and other social and economic partners. Students will be able to meet these players in the various events, organized in different campus locations by the teaching and research units linked to the program (ICT forum, industry days etc.)
The DSBI track focuses on the models and technologies linked to decision support systems. Emphasis is placed on semantics and unstructured data which now represents more than 80 % of all data handled in companies. This track addresses the technological changes paving the way for the next generation of decision support systems. Modules cover theoretical fundamentals, such as advanced data mining and machine learning, the models required to support unstructured data with decision support systems such as ontology and graphs, as well as the models required for decision making in complex situations.
This master's programs offer additional services. These programs require specific tuition fees in addition to the mandatory fees.
Tuition fees for the academic year:
- 4 000 € for European (UE) students
- 8 000 € for non european (non-UE) students
Some students may be eligible for a fee waiver.
The DSBI track is a specialization of the Erasmus Mundus IT4BI Master’s program.
Pièces justificatives à joindre à la candidature en ligne / List of documents you have to join to the online application :
- CV/Curriculum vitae (Obligatoire/Obligatory)
- Lettre de motivation/Letter of motivation (Obligatoire/Obligatory)
- Tous les relevés de notes des années/semestres validés depuis le bac à la date de la candidature /All transcripts of years / semesters validated from the baccalaureate to the date of application (obligatoire/obligatory)
- Attestation de niveau d'anglais (obligatoire pour les non anglophones) / Certificate of English level (compulsory for non-English speakers)
- Fiche de choix de M2 pour les candidats inscrits en M1 à l'université Paris-Saclay : à télécharger sur https://www.universite-paris-saclay.fr/fr/etre-candidat-a-nos-formations (obligatoire pour tous les candidats actuellement inscrits en M1 à l’Université Paris Saclay) / M2 selection card for candidates enrolled in M1 at Paris-Saclay University : to download on https://www.universite-paris-saclay.fr/en/apply-to-master-programs (obligatory for all candidates currently enrolled in M1 at Paris Saclay University).
- Curriculum UE (descriptifs des UE suivies) des deux dernières années / EU Curriculum EU descriptions for the last two years (Obligatoire/Obligatory)
La capacité d'accueil de cette formation est de 15 étudiants
Les modalités d'examen de la candidature sont les suivantes : Examen de dossier à déposer sur le site web de l'UPSaclay
Date d'ouverture de campagne 1 : 08/01/2018
Date de fermeture de campagne 1 : 30/06/2018
Date de fermeture de campagne 2 : 14/09/2018
Date de fermeture de campagne 2 : 29/09/2018
Dossier VAPP (Valorisation des Acquis Professionnels et Personnels)
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 (au bas de page)
Teaching language: english
Prior knowledge of the fundamentals of relational databases and data mining (statistics) is strongly recommended.