12 monthsProgramme duration
243 EURTuition Fee/year
Jan, SepStarting Month
Programme overview
Main Subject
Computer Science and Information Systems
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The DataScale programme focuses on the study of and proficiency in new data management and knowledge extraction architectures, from the very large data servers (data centres) to our countless connected objects (edge computing). It aims to provide students with a precise understanding of the technological and scientific challenges involved in the design of these new architectures and the development of Big Data applications using them. The complexity, heterogeneity, and distribution of data and processing must be taken into account as much as the reliability, security, and performance of the underlying data managers (RDBMS or NoSQL).
The skills acquired at the end of the programme follow three axes:
1) big data architectures, cloud and IoT, security and performance;
2) data integration and quality, data mining and knowledge extraction;
3) development and deployment of data-driven services and applications.
Students receive a common core curriculum along these three axes. This common core is supplemented by optional courses covering various topics such as data mining, data confidentiality, the semantic web, cloud computing, ambient data management, the Internet of Things or application development frameworks, opening up research perspectives associated with these different topics.
In order to apply to one of the programmes of the master, please select the programme you are interested in under the "Year 1 & 2 Master's programmes" tab .
The skills acquired at the end of the programme follow three axes:
1) big data architectures, cloud and IoT, security and performance;
2) data integration and quality, data mining and knowledge extraction;
3) development and deployment of data-driven services and applications.
Students receive a common core curriculum along these three axes. This common core is supplemented by optional courses covering various topics such as data mining, data confidentiality, the semantic web, cloud computing, ambient data management, the Internet of Things or application development frameworks, opening up research perspectives associated with these different topics.
In order to apply to one of the programmes of the master, please select the programme you are interested in under the "Year 1 & 2 Master's programmes" tab .
Programme overview
Main Subject
Computer Science and Information Systems
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The DataScale programme focuses on the study of and proficiency in new data management and knowledge extraction architectures, from the very large data servers (data centres) to our countless connected objects (edge computing). It aims to provide students with a precise understanding of the technological and scientific challenges involved in the design of these new architectures and the development of Big Data applications using them. The complexity, heterogeneity, and distribution of data and processing must be taken into account as much as the reliability, security, and performance of the underlying data managers (RDBMS or NoSQL).
The skills acquired at the end of the programme follow three axes:
1) big data architectures, cloud and IoT, security and performance;
2) data integration and quality, data mining and knowledge extraction;
3) development and deployment of data-driven services and applications.
Students receive a common core curriculum along these three axes. This common core is supplemented by optional courses covering various topics such as data mining, data confidentiality, the semantic web, cloud computing, ambient data management, the Internet of Things or application development frameworks, opening up research perspectives associated with these different topics.
In order to apply to one of the programmes of the master, please select the programme you are interested in under the "Year 1 & 2 Master's programmes" tab .
The skills acquired at the end of the programme follow three axes:
1) big data architectures, cloud and IoT, security and performance;
2) data integration and quality, data mining and knowledge extraction;
3) development and deployment of data-driven services and applications.
Students receive a common core curriculum along these three axes. This common core is supplemented by optional courses covering various topics such as data mining, data confidentiality, the semantic web, cloud computing, ambient data management, the Internet of Things or application development frameworks, opening up research perspectives associated with these different topics.
In order to apply to one of the programmes of the master, please select the programme you are interested in under the "Year 1 & 2 Master's programmes" tab .
Admission Requirements
72+
5.5+
Compulsory supporting documents
- Certificate of French (compulsory for non-French speakers).
- Motivation letter.
- Curriculum Vitae.
- All transcripts of the years / semesters validated since the high school diploma at the date of application.
- VAP file (obligatory for all persons requesting a valuation of the assets to enter the diploma).
1 Year
Jan
Sep
- Candidates are required to submit references or letter(s) of recommendation for acceptance
- Candidates are required to submit an essay(s) for acceptance
Tuition fees
Domestic
243 EUR
International
243 EUR
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