24 monthsProgramme duration
5,950 EURTuition Fee/year
15 Jun, 2026Application Deadline
SepStarting Month
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MEng
Study Level
Masters
Study Mode
On Campus
To train specialists with knowledge of mathematical statistics and computer science related to the analysis of big data, who are familiar with the functionalities of modern business analytics software tools, and who are able to apply methods of statistical analysis, statistical modelling and forecasting to solve problems that arise in scientific research and practice.
Knowledge • Knowledge of the connections between data analysis, probability theory, and mathematical statistics, as well as linear and nonlinear regression and classification models. • Comprehension of the mathematical models used in statistical data analysis, as well as methods for selecting these models, evaluating their parameters, and assessing model quality. • Knowledge of programming languages (R and Python), their possibilities for data analysis, and mathematics and computer science methods suitable for creating models for data analysis of various scales
Ability to Perform Research • Proficiency in creating mathematical models for solving problems in finance, economics, and other scientific fields, and justify their suitability. • Ability to create mathematical models for both small and large-scale data, evaluate their parameters, check the model's suitability for the available data, and compare multiple models with each other.
Special Skills • Ability to select appropriate models for the economic objects and social phenomena under research, apply them using statistical software, solve practical business tasks, summarise and interpret research results. • Ability to program in R and Python, prepare data for analysis, create statistical models, evaluate their parameters, prepare the results of statistical research for further analysis, and present them to the public.
Social Skills • Ability to present scientific research to specialists and non-specialists in a clear and argumentative way, critically evaluate, and discuss it. • Ability to work in an interdisciplinary and international team, participate in professional networks.
Personal Skills • Ability to study and improve independently in selected areas of mathematics, statistics and their applications, and to plan the learning process throughout life. • Ability to make decisions independently, assess their consequences and their complexity.
Knowledge • Knowledge of the connections between data analysis, probability theory, and mathematical statistics, as well as linear and nonlinear regression and classification models. • Comprehension of the mathematical models used in statistical data analysis, as well as methods for selecting these models, evaluating their parameters, and assessing model quality. • Knowledge of programming languages (R and Python), their possibilities for data analysis, and mathematics and computer science methods suitable for creating models for data analysis of various scales
Ability to Perform Research • Proficiency in creating mathematical models for solving problems in finance, economics, and other scientific fields, and justify their suitability. • Ability to create mathematical models for both small and large-scale data, evaluate their parameters, check the model's suitability for the available data, and compare multiple models with each other.
Special Skills • Ability to select appropriate models for the economic objects and social phenomena under research, apply them using statistical software, solve practical business tasks, summarise and interpret research results. • Ability to program in R and Python, prepare data for analysis, create statistical models, evaluate their parameters, prepare the results of statistical research for further analysis, and present them to the public.
Social Skills • Ability to present scientific research to specialists and non-specialists in a clear and argumentative way, critically evaluate, and discuss it. • Ability to work in an interdisciplinary and international team, participate in professional networks.
Personal Skills • Ability to study and improve independently in selected areas of mathematics, statistics and their applications, and to plan the learning process throughout life. • Ability to make decisions independently, assess their consequences and their complexity.
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MEng
Study Level
Masters
Study Mode
On Campus
To train specialists with knowledge of mathematical statistics and computer science related to the analysis of big data, who are familiar with the functionalities of modern business analytics software tools, and who are able to apply methods of statistical analysis, statistical modelling and forecasting to solve problems that arise in scientific research and practice.
Knowledge • Knowledge of the connections between data analysis, probability theory, and mathematical statistics, as well as linear and nonlinear regression and classification models. • Comprehension of the mathematical models used in statistical data analysis, as well as methods for selecting these models, evaluating their parameters, and assessing model quality. • Knowledge of programming languages (R and Python), their possibilities for data analysis, and mathematics and computer science methods suitable for creating models for data analysis of various scales
Ability to Perform Research • Proficiency in creating mathematical models for solving problems in finance, economics, and other scientific fields, and justify their suitability. • Ability to create mathematical models for both small and large-scale data, evaluate their parameters, check the model's suitability for the available data, and compare multiple models with each other.
Special Skills • Ability to select appropriate models for the economic objects and social phenomena under research, apply them using statistical software, solve practical business tasks, summarise and interpret research results. • Ability to program in R and Python, prepare data for analysis, create statistical models, evaluate their parameters, prepare the results of statistical research for further analysis, and present them to the public.
Social Skills • Ability to present scientific research to specialists and non-specialists in a clear and argumentative way, critically evaluate, and discuss it. • Ability to work in an interdisciplinary and international team, participate in professional networks.
Personal Skills • Ability to study and improve independently in selected areas of mathematics, statistics and their applications, and to plan the learning process throughout life. • Ability to make decisions independently, assess their consequences and their complexity.
Knowledge • Knowledge of the connections between data analysis, probability theory, and mathematical statistics, as well as linear and nonlinear regression and classification models. • Comprehension of the mathematical models used in statistical data analysis, as well as methods for selecting these models, evaluating their parameters, and assessing model quality. • Knowledge of programming languages (R and Python), their possibilities for data analysis, and mathematics and computer science methods suitable for creating models for data analysis of various scales
Ability to Perform Research • Proficiency in creating mathematical models for solving problems in finance, economics, and other scientific fields, and justify their suitability. • Ability to create mathematical models for both small and large-scale data, evaluate their parameters, check the model's suitability for the available data, and compare multiple models with each other.
Special Skills • Ability to select appropriate models for the economic objects and social phenomena under research, apply them using statistical software, solve practical business tasks, summarise and interpret research results. • Ability to program in R and Python, prepare data for analysis, create statistical models, evaluate their parameters, prepare the results of statistical research for further analysis, and present them to the public.
Social Skills • Ability to present scientific research to specialists and non-specialists in a clear and argumentative way, critically evaluate, and discuss it. • Ability to work in an interdisciplinary and international team, participate in professional networks.
Personal Skills • Ability to study and improve independently in selected areas of mathematics, statistics and their applications, and to plan the learning process throughout life. • Ability to make decisions independently, assess their consequences and their complexity.
Admission Requirements
60+
Bachelor's degree or its equivalent (official transcripts required) in a relevant field with minimum 60% CGPA and English language proficiency level B2.
Record an interview.
15 Jun 2026
2 Years
Sep
- Candidates are required to submit references or letter(s) of recommendation for acceptance
- Candidates are required to submit an essay(s) for acceptance
Tuition fees
Domestic
5,500 EUR
International
5,950 EUR
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