|Nominal duration||2 years (120 ECTS)|
|Awards||MSc (Master of Mathematical Sciences)|
Undergraduate diploma (or higher)
A minimum of a three years University Bachelor’s degree in Engineering or adequate.
The entry qualification documents are accepted in the following languages: English / Russian.
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.
The documents must be legalised (Apostille)by the Ministry of Foreign Affairs of the country where the documents were issued. This requirement does not apply for the documents issued in the EU and Belarus, Ukraine.
It is required that you send verified copies of the entry qualification documents directly to the university by postal mail. Important! Never send original documents by post!
International Studies Office
IELTS 6.0+, TOEFL IBT 80+ or CEFR B2+, or equivalent (we can organise English test ourselves or by our authorised partners).
If your previous studies have been fully in English and it is marked on your degree certificate or transcript, or noted in a confirmation from the school which confirms that your studies have been fully in English language, additional English test is not required.
The study programme is focused on business big data, synergy in development of mathematical and computer science skills and competencies, development of mathematical models for business development decisions. Graduates are able to analyse the business big data, to identify business problems, optimize business processes, apply acquired knowledge and to create mathematical models and algorithms for business decisions and business insights development.
Top reasons to study:
1. KTU launched the first in Lithuania study programme for business big data analysis with strong engagement of industry partners to facilitate growing demand for the specialists in the field.
2. Practical seminars are conducted by Lithuanian and international experts from leading business companies (Western Union, Adform, Barclays, Execaster, etc.).
3. Case-based teaching and problem-based learning facilitates understanding of ongoing challenges and application of real-life solutions using Spark, Python, Scala, SAS, R software.
Analysis of business big data and decision making
Big data mining methods
Multivariate statistical analysis models
Optimisation and decision making
Time series analysis
Financial markets models
Analysis of business processes and identification of problems
Strategic Business Analysis
Project of business external data analytics
Project of business internal data analytics
Analytics of finance and accounting data
Financial management decisions
Business logistics analytics
Design of business systems, risk evaluation, prediction and optimisation
Business risk and uncertainty analytics
Marketing decisions modeling
Tax system simulation
Development of business big data analytic tools and design of software
Big data analytic tools
Business information technology
Information systems requirements analysis and specification
Metadata analysis and information portals
for TRANSFER (only transfer students are accepted)