Masters Degree in Big Data in Romania

View all Master Programs in Big Data in Romania

Big Data

A master's degree is a postgraduate academic degree. One must already have an undergraduate degree to apply for a master's program. Most master's degree program would require students to complete a master's thesis or research paper.

Big data is an important field of study for any business that handles data sets far larger than common software tools can handle. The applications of big data are used in healthcare, the military, education, manufacturing and many other industries.

Romanian university qualifications highly appreciated and recognized in Europe and beyond, lowest tuition fees and living cost in Europe. The Romanians have an old and rich history, especially in the capital Bucharest with its 2 million people. International students willing to study in Romania can apply either to the Ministry of Education and Research or to the chosen Romanian university, in order to receive the Letter of Acceptance.

Masters Degree in Big Data in Romania

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Master in High Performance Computing and Big Data Analytics

UNIVERSITATEA BABEȘ-BOLYAI
Campus Full time October 2019 Romania Cluj-Napoca

The master’s program aims at providing students with the appropriate tools for further doctoral studies and professional activity. [+]

The master’s program aims at providing students with the appropriate tools for further doctoral studies and professional activity.

Program objectives

Acquisition of theoretical, applicative and practical knowledge in:

complex systems modeling based on mathematical concepts and methods, and on programming concepts and techniques. programming and usage on/of computation systems, especially those of high performance, which are necessary for solving real-life problems and for simulating complex problem solutions. exploitation (data-analysis, knowledge-discovering) and visualization of „big data” for computation problems, statistical interpretations, decision processes, or for scientific instruments. applicative scientific domains where high-performance systems are used. analysis and improvement of software processes. professional modeling for teamwork as well as interdisciplinary approaches to research and development. Core courses Programming Paradigms Parallel and Distributed Operating Systems Formal Modelling of Concurrency Advanced Methods in Data Analysis Functional parallel programming for big data analytics Models in parallel programming General Purpose GPU Programming Workflow Systems Resource-aware computing Data Mining Grid, Cluster and Cloud Computing Knowledge Discovery in Wide Area Networks Admission requirements ... [-]