In order to successfully obtain a Masters qualification, you will need to obtain a number of credits by passing individual modules. Most taught Masters will have a number of core modules which you must take and pass in order to obtain the qualification. The assessment of research Masters is almost always entirely by a single dissertation module or project.
One of the greatest aspects of technology is that when it is embedded in machines and devices, most of the time the individual operating the machine or device does not need to understand the specifics of how the technology works. For example, someone using a computer does not need to understand the mechanics of the hard drive to benefit from using it.
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.
Cluj-Napoca city is the capital of Cluj County in Romania and the 2nd most populated after Bucharest. It is a metropolitan area with a population of over 300,000 residents. It has around 150 pre-university educational institutions.
Request Information Master's Degrees in Technology Studies in Cluj-Napoca in Romania 2018/2019
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 ... [-]