Social Data Science
| Study location | Hungary, Budapest |
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| Type | Master, full degree studies |
| Nominal duration | 2 semesters |
| Study language | English |
| Course code | Economic Science |
| Entry qualification | Bachelor diploma (or higher) Read this information carefully Entrance exam Recognition/legalisation requirements This means your qualification must be deemed at least “equivalent” to a Hungarian high school diploma (for entry onto a BA/BSc) or a Hungarian Bachelor’s degree (for entry onto an MA/MSc/MBA). Credit requirements Please make sure you meet the minimum requirements for this programme before applying. Your application will be rejected if you don’t meet the credit requirements – it is your responsibility calculate your credits in ECTS and make an initial analysis before applying For credit requirements, see our website: www.uni-corvinus.hu/main-page/hello-corvinus/how-to-apply/ma-msc-programs-application-information/?lang=en The entry qualification documents are accepted in the following languages: English. Often you can get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original. You must take the original entry qualification documents along with you when you finally go to the university. |
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| Language requirements | English “Your English language skills should be a minimum of B2. This is assessed by the entrance exam.” |
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| Other requirements | At least 2 reference(s) should be provided. |
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| More information |
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Overview
“Be among the first students worldwide in a new and growing interdisciplinary field, taught by internationally recognized scientists and researchers.”
Description
We have never had more data available to help address society’s most pressing issues. Thus, knowing what questions to ask from data and how to answer them has never been more valuable. Do you want to know how exceptional new ideas, political movements, or even music pieces spread around the world? Do you want to better understand causes and consequences of phenomena like economic growth and inequality? Have you wondered why some teams, firms, or places are consistently more successful than others? Do you wonder how cities evolve and shape the lives of their inhabitants? Then this is the program for you!
Our aim is that by the end of your year here you will see the world differently. Nobel laureate Herbert Simon once said that a “wealth of information creates a poverty of attention”. In other words, good decision making in the age of data requires us to effectively distinguish between valuable information and useless facts. This interdisciplinary programme will teach you how to do this: it combines computational, statistical, and social science skills in a way that prepares you to critically approach any problem where data science can have value.
We welcome applications from students with backgrounds in either the natural sciences and engineering (i.e. mathematics, physics, engineering, computer science, information systems, data science) or in the quantitative social sciences (economics, sociology). Some prior experience in coding is essential.
Entry requirements:
Undergraduate degree meeting minimum credit requirements (see above)
B2 Level English (see above)
Entrance exam:
The entrance exam is an online written test and an interview organized by Corvinus University of Budapest.
You are not required to do the written test if you have one of the following:
- One of the following tests with the following minimum scores: GMAT (500), GRE (300), NMAT (150) or GMAT FE (485).
- A 5 (A) or 4 (B) grade degree from an AACSB/EQUIS accredited or CEMS member university.
Please note that even if you have either of the above you will still have to take part in the interview.
Note: meeting the minimum score does not guarantee admission, but you will be ineligible if you don’t meet this requirement. The actual threshold will be set by the Dean in late April. This includes the international tests and the accredited degree. Your test score or degree grade will be converted into an admission score.