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Specialized Master in data science, Big data

  • academic year
    2019-2020
Specialized Master in data science, Big data

This formation is taught in english.

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  • Programme title
    Specialized Master in data science, Big data
  • Programme mnemonic
    MS-BGDA
  • Programme organised by
    • Faculty of Sciences
  • Degree type
    Advanced masters
  • Tier
    2nd cycle
  • Field and branch of study
    Sciences and technics/Sciences
  • Schedule type
    Daytime
  • Languages of instruction
    english
  • Theoretical programme duration
    1 year
  • Campus
    Plaine/Solbosch
  • Category / Topic
    Sciences and technics - Sciences
  • Jury President
    Thomas VERDEBOUT
  • Jury Secretary
    Davy PAINDAVEINE

Details

General information

Degree type

Masters spécialisés

Theoretical programme duration

1 year

Learning language(s)

english

Schedule type

Daytime

Campus

Plaine/Solbosch

Category(ies) - Topic(s)

Sciences and technics - Sciences

Organising faculty(s) and university(ies)

Contacts

+32 2 650 58 92

Presentation

You have already a master degree and good knowledges in computer sciences or in statistics and you are interested by their applications. Then the present master is a natural choice to improve your skills and become a specialist in massive data analysis. The program we propose here is fully taught in english and therefore opens to the international job market.

In particular, the objective of the master is to improve the following skills:

  • Perform a research project or an applied innovation in computer sciences or in statistics.

  • Design and implement applications based on artificial intelligence and learning techniques.

  • Clearly communicate to various types of audiences conclusions or results of a project in computer sciences, statistics or econometrics.

  • Be able to develop new skills by yourself.

  • Be able to be rigorous, independent, ethic, creative and aware of the impact of the results obtained for a company or for the society in general.

The specialized master in data science, big data provides an interdisciplinary training in data analysis (model choice, forecast, inference, learning) of big data. The program has been constructed in order to teach both statistical and computer sciences techniques. We furthermore propose lectures in econometrics to let students deal with quantitative practical aspects. The student who wants to complete his/her master by a internship will clearly benefit form the fact that Brussels is full of companies interested by the profile.

Several faculties are involved in the master: the Faculty of Sciences, the Brussels School of Engineering and the Solvay Brussels School of Economics and Management from ULB and also partners for the VUB. This is clearly an asset since it reinforces the interdisciplinary aspect of the master which is supported by various important teams of researchers from the ULB and the VUB:

  • ECARES, Solvay Brussels School of Economics and Management

  • IB2 (Interuniversity Institute of Bioinformatics in Brussels), ULB/VUB

  • IRIDIA, Brussels School of Engineering

  • LISA, Brussels School of Engineering

  • Machine Learning Group, Faculty of Sciences

  • Mathematical Statistics Group, Faculty of Sciences

  • WIT, Brussels School of Engineering

Access conditions

Programme

What's next ?

Prospects

The present master has been created to deepen your knowledge and understanding of emerging, state-of-the-art database technologies. Indeed, the intensive use of computers and the internet in the beginning of the present century has a clear impact on the way data have to be collected and treated. In many situations, practitioners have to deal with massive databases (« Big data »).

Data science finds its roots in many applications: genomics and high scale DNA sequencing generate tons of data at many different biological levels; the use of social networks, mobile phones, tablets generate data every single second; robots and industrial equipments are nowadays equipped with sensors that provide a huge amount of information and therefore huge databases. In economics and in finance, practitioners have to deal with real-time forecasts based on high-frequency data (production, trade, market data).

The master is a natural preparation for the following jobs: "data scientist", "data manager", "analytics manager" or simply "statistician" or "computer scientist" that are increasingly demanded by companies.