MScIT for Business Data Analytics
Study location | Hungary, Budapest |
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Type | Master, full-time |
Nominal duration | 3 semesters (2 paid semesters) |
Study language | English |
Awards | MSc |
Tuition fee | €6,400 per semester No payment for semester 3. |
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Application fee | €100 one-time This is a non-refundable fee. |
Registration fee | €900 one-time This is a one-time registration fee for non-EU citizens. |
Entry qualification | First or second class Bachelor's degree in any field of study Min. one semester of mathematics, statistics, or computing/IT The entry qualification documents are accepted in the following languages: English / Hungarian. 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 MSc applicants are required to pass IBS’ own English Language Placement Test that consists of a 100 minute test and an Orientation Interview. If the applicant has a certificate of
or if the applicant is
the applicant is not required to take the written test, only the Orientation Interview. |
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More information |
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Overview
IBS’ conversion master’s programme welcomes students from all areas who would like to become professionals with strong business foundations. Get extensive data analytics skills to improve your employability and become a more valuable member of the organisation that you work for!
Programme Content
The goal of the MSc in IT for Business Data Analytics programme is to (re-)train professionals who will be able to occupy junior and mid-level data analyst positions, thanks to their ability to import, inspect, clean, transform, validate, model, or interpret collections of data with regard to the business goals of the company as well as to their ability to use different algorithms and IT tools as demanded by the situation and the current data.
Those graduating from the programme can prepare reports in the form of visualizations such as graphs, charts, and dashboards. The programme is therefore a conversion programme aimed at those seeking career advancement or career change and one that will train data professionals with strong business foundations.
Key areas of studies
Python for data analytics, data mining and machine learning (with optional modules on R, text mining and natural language processing, and advanced forecasting), databases for data science and analytics, business intelligence for data-driven management (using Tableau and/or Power BI), skills for data analysts (GitHub for collaboration, basics of survey research and A/B testing, communication skills), business skills (with optional modules on human-resource management, marketing, team management, and market and competition analysis), decision-making and analytical skills, etc.
Central European Time
Central European Time
Central European Time
Central European Time