BIG DATA ANALYTICS
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 labour market.
Benefits of the programme
- 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.
- Flexible study and payment schedule.
- A wide range of discounts.
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Programme director
Dr. phys., doc. Ivars Godmanis
Phone: +371 26626187; e-mail: [email protected]
Programme curriculum
| Module No. 1: Economic and Business Processes 12 credits (18 ECTS) | Module No. 2: Big Data Management 14 credits (21 ECTS) |
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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 |
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) | |
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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 |
The curriculum of Study Programme
Self assessment of the programme
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.
Click here and see application requirements for international students
International opportunities
Erasmus+ study mobility
* Any full-time student of the Master's programme in Big Data Analytics who has completed at least one year of study can go to the Erasmus+ exchange programme.
* A student can go to study for 1 or 2 semesters at one of the RISEBA partner universities. The duration of study mobility is 2-12 months.
* The student does not have to pay for the period spent in the study and practice exchange programme abroad, the tuition fee is covered by the partner university, but the student continues to pay the RISEBA tuition fee. For the period spent abroad during the mobility, the student is awarded an Erasmus+ scholarship to cover transport and accommodation costs.
* Erasmus+ Internship Mobility means that a student can do an internship in one of the companies they are interested in in one of the Erasmus+ programme countries. The student receives an Erasmus+ scholarship for this internship period. The duration of the internship mobility is 2-12 months.
Find out more about Erasmus+ and apply here!
RISEBA main campus: Meža str. 3, Riga, LV-1048, tel. +371 67500265, [email protected]
