M.Sc.Big Data Analysis
| Studienort | Lettland, Riga |
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| Akademischer Bereich | Business and administration (ISCED 34) Management studies (JACS N200) |
| Art | Master, Vollzeit |
| Nominale Dauer | 2 Jahre (90 ECTS) |
| Studiensprache | Englisch |
| Auszeichnungen | M.Sc. (Social sciences master's degree in economics) |
| Studiengebühren | 5.700 € pro Jahr |
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| Bewerbungsgebühr | 200 € einmalig |
| Anmeldegebühr | Zu bestätigen You need to choose an individual service package. Please contact the center curator or your agent and consult. You become a part of student union and ambassador program automatically after you will get Base or Standard or VIP status. *Do not forget to ask discount |
| Einstiegsqualifikation | Gymnasium / Sekundarstufe (oder höher) Please provide the secondary school leaving certificate in the original language. If the diploma is not issued in English, a certified translation should be provided. The document must be legalised/apostilled. Sie müssen die Originalnachweise über die Eingangsqualifikation mitnehmen, wenn Sie schließlich zur Universität gehen. It is necessary to have notarized certified documents translated, legalized and apostilled. |
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| Gebietsanforderungen | Bewerbungen aus den folgenden Gebieten werden NICHT akzeptiert (basierend auf der Staatsbürgerschaft): Bangladesch, Irak, Jemen, Pakistan. |
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| Sprachanforderungen | Englisch IELTS score 6.0+, TOEFL 78 + |
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| Sonstige Voraussetzungen | Mindestens 1 Referenz/en soll/en angegeben werden. Employer reference permitted Ein Motivationsschreiben muss Ihrer Bewerbung hinzugefügt werden. 1. Entrance examination in English language (only for those who applied to study in English); 2. RISEBA Admissions Test. |
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Übersicht
The objective of the academic master study programme Big Data Analytics is to provide studies that correspond to the newest technological solutions, recommendations of professional organisations and the demand from IT and ICT companies, banks, trade and public sectors for specialists in the new Big Data analysis field, as well as to prepare highly skilled and competitive specialists for the Latvian and global labor market.
The only programme in Latvia offering to study Big Data analytics in the field of economic processes.
RISEBA studies provide practical experience and the opportunity to learn from professionals of their respective fields.
The subjects of the programme will prepare students for employment in several economic sectors where there is an aggregation of a large amount of data.
Case studies, problem-solving and analytical research are all a part of the RISEBA learning process.
The programme has been developed in collaboration with employers and market requirements of several industries.
Field professionals contribute to the study process.
Individual approach to each student.
Programmstruktur
Module No. 1: Economic and Business Processes 12 credits (18 ECTS)
Introduction to Big Data Analysis: 1 credit
EU Politics and Economy: 1 credit
Strategic Management: 2 credits
Business Optimisation and Decision-Making: 2 credits
Project Management in Organisations: 2 credits
Economic and Mathematical Modelling: 2 credits
Business Risk Management: 2 credits
Module No. 2: Big Data Management 14 credits (21 ECTS)
Big Data Acquisition Methods: 2 credits
Data Management and Usage: 2 credits
Big Data Research Methods: 2 credits
Data Security Management: 2 credits
Open Innovation and Protection of Intellectual Property: 2 credits
Data Visualisation Methods: 2 credits
Artificial Intelligence in Business: 2 credits
Module No. 3: Methods of Big Data Analysis, 16 credits (24 ECTS)
Information System Requirement Analysis: 2 credits
Multivariant Models of Static Analysis: 2 credits
Blockchain Technologies: 2 credits
Forecasting and Modelling: 2 credits
Practical Project. Using data analysis software: 6 credits
Karrieremöglichkeiten
Graduates of the master’s programme will:
- be able to use different data acquisition and management methods;
- know the newest technological solutions;
- be able to use methods of Big Data analysis and visualisation;
- be able to use the acquired knowledge for economic process analysis and business growth.