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Mathematics
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Summary of the Profile
General Description:
Objective(s) of a study programme:
The aims of the study Programme – to prepare Masters of Mathematics: who have the relevant knowledge of mathematics substantiated with the results of scientific research , who are able to integrate and responsibly apply it in new situations, while conducting scientific research of chosen area and/or in the work of a high qualification analyst, a specialist of modelling and data analysis; who have the skills of individual creative work, lifelong learning, critical assessment of activity and efficient communication.
Learning outcomes:
Generic competencies developed:
After analysing and synthesizing scientific and subject-based literature, as well as evaluating research field, a student will be able to identify and substantiate independently the issues and the need of scientific research, to choose the appropriate methodology of research; will be able in written and oral form in native and foreign language to convey subject-based information and summarized research results to professionals and general public. A student will be able to work individually and lead a team, to assess objectively and comprehensively his/her own and team’s performance results, to take responsibility for performance quality; will perceive the importance of life-long learning, will choose independently the self-development direction, will generate modern ideas of professional activity, and will be able to evaluate the advancement.
Subject specific competencies developed:
A student will be able to analyse multifaceted information, to generalize it, to determine functional relationships among different mathematical values, to describe the processes under analysis by using mathematical language. A student will be able to prepare determinant, stochastic and differential equations’ mathematical models for physical and social processes, to describe the proceeding of these processes, as well as their characteristics; by thinking logically and analytically, a student will be able to choose and evaluate the alternative ways of model solution, to solve the problems of adequacy and optimality. A student will be able to initiate and conduct independently scientific research, to process research data, to analyse, synthesize, assess and interpret research results, to formulate and substantiate the conclusions, to provide innovative recommendations and forecasts; will be able to use specialized software in solving the tasks of data analysis, optimization, as well as the tasks of implementation of mathematical models.
Learning outcomes:
Graduate with the Master’s degree in Mathematics manifests one's knowledge and skills solving non-standard tasks in the new (non-typical) environment and conducting scientific research; the graduate can work as a professional analyst or a modelling and data analysis specialist and use one’s professional qualification implementing innovations. He / she is practically aware of scientific research methodology and is able to integrate knowledge, manage difficult situations, make reasonable conclusions and present them clearly. Master is able to work individually and in a team, take responsibility for the quality of one's own activities as well as the subordinate employees’ activities, be responsible for the quality assessment and its development.
Activities of teaching and learning:
The choice of study methods is determined by competences developed by students, learning outcomes, as well as the student-centred learning. The competences acquired during the studies of subjects will be consistently developed and deepened by mastering the abilities of a higher level. At the beginning of studies, study methods (lectures, interactive lectures, practices, laboratory works, etc.) will be used, while, in senior semesters, activating teaching methods, the methods emphasizing a student’s individual learning, substantiated by scientific research, problem solving (discussion, analysis of research article, case study, project , preparation of presentations, group work, individual consultations, etc.) will be used.
Methods of assessment of learning achievements:
The criteria of assessment of students’ achievements are aimed to achieve expected learning outcomes and are related to the learning outcomes of entire study programme. The accumulative (except Research Work in Science and Master Graduation Thesis) assessment with leverage coefficients applied to different task types will be used to assess the knowledge and abilities acquired by students. The following assessment methods will be used: examinations, practices, case analysis, presentations, reports, self- evaluation, peer evaluation in distance environment, colloquiums, defence of laboratory works, tests, individual homework, research papers, etc. Each teacher, while creating threshold level and assessment criteria of a subject, will take into consideration the aims of a subject and knowledge, abilities and competences necessary for the qualification. The examination will be the final form of evaluation in all subjects. In the basic subjects of Mathematics, it will be strived for a typical level of study achievements, i.e., we will strive that students would know the basic theories and principles of mathematics, would be able to apply the knowledge in solving standard and nonstandard problems of study field or the problems related to professional activity, would be able to independently collect, assess and interpret the data of study field necessary to take decisions, would have learning skills necessary for further studies and individual learning.
Framework:
Study subjects (modules), practical training:
The volume of the subjects in the field of Mathematics is 95 credits. After acquiring thorough knowledge of analytic number theory, function, group theory, theory of differential equations, a student will be able to apply them creatively in solving practical tasks, as well as conducting scientific research. A student will master the modern methods of multidimensional statistical analysis, reliability analysis, optimization, graph theory, will be able to apply them in modelling real processes, as well as in analysing the results; after acquiring deeper knowledge of mathematical modelling, will be able to use it in further studies of interdisciplinary subjects or in professional activity while implementing the innovations. The volume of the specialization subjects is 25 credits. After studying subjects reliability analysis, optimization methods in economics, big data mining and analysis, bussines intelligence tools, student will be able to use specialized software in solving the tasks of data analysis and optimization.
Specialisations:
Big Data Analytics. A Master of Mathematics gains additional competences and skills required for a specialist of big data analysis to have. A graduate is able to apply modern methods of analysis and prediction as well as software for the analysis of the big business data, to provide recommendations based on mathematical methods for management, optimisation or prediction of various business processes.
Optional courses:
It is possible to deepen the acquired knowledge by choosing a specialization.
Distinctive features of a study programme:
The study programme is oriented towards mastery of not only the classical (number theory, theory of differential equations, multidimensional statistical analysis), but also integrated mathematical, big data analysis and business analytics knowledge, its application for optimisation and prediction of business processes. Theoretical and practical subjects keep a balance: in the first semester the basic knowledge and skills broadening and deepening subjects are studied, while in third - only specialization. There is a possibility for the distance study of certain subjects.
Access to professional activity or further study:
Access to professional activity:
The gained qualification degree enables the graduates to work as a lecturer or a researcher at universities and colleges, an analyst or a specialist on big data analysis and modelling in financial institutions, consulting, logistics or trade companies, in private enterprises, public sector, research centres as well as in other areas requiring deep knowledge of mathematics and information technologies.
Access to further study:
Access to the third cycle studies
