Type:
Master
Speciality:
056101.09.7 - Mathematics
Specialisation:
056101.09.7 - Mathematics and Applications
Programme academic year:
2024/2025
Mode of study:
Full time
Language of study:
Հայերեն
1. Admission criteria/requirements
The admission is made according to the Yerevan State University master's degree admission regulations.
The applicant for the program must have a bachelor's degree or equivalent.
The admission of applicants with a bachelor's degree or equivalent qualification in the given profession is done on a competitive basis, based on the results of the progress shown during the previous studies.
The admission of applicants with a bachelor's degree or equivalent qualification in another specialty is done on a competitive basis, based on the results of the exams conducted in accordance with the exam program for the bachelor's summary certification of the given specialty.
The applicant for the program must have a bachelor's degree or equivalent.
The admission of applicants with a bachelor's degree or equivalent qualification in the given profession is done on a competitive basis, based on the results of the progress shown during the previous studies.
The admission of applicants with a bachelor's degree or equivalent qualification in another specialty is done on a competitive basis, based on the results of the exams conducted in accordance with the exam program for the bachelor's summary certification of the given specialty.
2. Programme Objectives
The programme is aimed at:
·to develop students' professional skills in mathematical analysis and theory of functions, topological vector spaces and operator theory;
to help students develop their theoretical knowledge and practical skills in the fields of algebra, real and complex analysis, probability theory and statistics, differential equations, functional analysis.
·to develop students' professional skills in mathematical analysis and theory of functions, topological vector spaces and operator theory;
to help students develop their theoretical knowledge and practical skills in the fields of algebra, real and complex analysis, probability theory and statistics, differential equations, functional analysis.
3. Educational outcomes of the programme
Upon completion of the course, the student will be able to:
- list the elements of the theory of fields, rings, groups, algebras; point out the current problems in these areas;
- present the main classical algorithms, the basics of signal processing;
- reproduce the properties of trigonometric and orthogonal series, bases in general Banach spaces;
- reproduce the methods of model-based design, the main problems of equations of mathematical physics;
- present probabilistic models corresponding to random phenomena, present industrial model problems;
- explain the mathematical concepts related to information technology;
- construct algebraic models, implement various algebraic algorithms in practice;
- apply the spectral decomposition of a normal operator, apply factorization methods for solving differential and integral equations, apply various numerical methods;
- construct wavelet bases and apply them in the theory of signal processing, study the convergence of Fourier series of some functions, implement fast Fourier algorithms, make approximations in the complex domain;
- analyze and apply probabilistic models, apply methods of mathematical statistics in econometrics, make predictions;
- build mathematical models for problems arising in various fields, research and propose solutions;
- build effective algorithms for solving various problems using programming tools, use programming packages for solving theoretical and applied problems.
- process, analyze the obtained results, prepare reports presenting the results of research, conduct scientific debates;
- analyze the existing problems and propose ways to solve them, apply the knowledge in solving the problems related to the field;
- choose the necessary research methods and adapt the existing methods to the study of a specific problem, use scientific publications and data on the Internet, collect information in the field of specialization.
4. Assessment methods
· written and oral midterm exams,
· written and oral midterm tests,
· final oral exams,
· oral exams without current assessment,
· reports,
papers.
· written and oral midterm tests,
· final oral exams,
· oral exams without current assessment,
· reports,
papers.
5. Graduates future career opportunities
Graduates of the programme can be employed as lecturers, assistants or researchers in universities:
YSU
Armenian State Pedagogical University,
State Engineering University of Armenia (Polytechnic) and its branches in Gyumri, Vanadzor, Kapan, Goris,
Institute of Mathematics of the National Academy of Sciences of the Republic of Armenia,
State University of Economics of Armenia,
National Agrarian University of Armenia,
Gavar State University,
Gyumri State Pedagogical Institute,
Goris State University,
Ijevan branch of Yerevan State University,
European Educational Regional Academy,
Armenian-Russian University,
French University in Armenia,
American University of Armenia,
private universities, branches of foreign universities in Armenia,
as well as carry out activities in the fields of information technologies, developing and implementing algorithms, to work in various research institutions in the fields of mathematics, mechanics, physics.
YSU
Armenian State Pedagogical University,
State Engineering University of Armenia (Polytechnic) and its branches in Gyumri, Vanadzor, Kapan, Goris,
Institute of Mathematics of the National Academy of Sciences of the Republic of Armenia,
State University of Economics of Armenia,
National Agrarian University of Armenia,
Gavar State University,
Gyumri State Pedagogical Institute,
Goris State University,
Ijevan branch of Yerevan State University,
European Educational Regional Academy,
Armenian-Russian University,
French University in Armenia,
American University of Armenia,
private universities, branches of foreign universities in Armenia,
as well as carry out activities in the fields of information technologies, developing and implementing algorithms, to work in various research institutions in the fields of mathematics, mechanics, physics.
6. Resources and forms to support learning
The following supporting resources can be used in the learning process:
distance learning and online lectures,
electronic resources.
distance learning and online lectures,
electronic resources.
7. Educational standards or programme benchmarks used for programme development
· RA Government Decree N 714-N of July 7, 2006, on approving the national framework for qualifications of the Republic of Armenia
· "Mathematics" sectoral framework of qualifications, 2022.
· European Qualifications Framework, 2008.
· The professional course programs of the Departments of Higher Algebra, Theory of Probability, Theory of Functions and Functional Analysis of the Faculty of Mechanics and Mathematics of Moscow State University
“International Master Program in Mathematical Physics” master's program of the leading research center of CY Cergy Paris University.
· "Mathematics" sectoral framework of qualifications, 2022.
· European Qualifications Framework, 2008.
· The professional course programs of the Departments of Higher Algebra, Theory of Probability, Theory of Functions and Functional Analysis of the Faculty of Mechanics and Mathematics of Moscow State University
“International Master Program in Mathematical Physics” master's program of the leading research center of CY Cergy Paris University.
8. Requirements for the academic staff
• master's degree and/or scientific degree in the relevant field,
• master modern teaching methods and tools,
• be able to use the YSU learning management system,
• provide students with modern literature and articles,
• knowledge of interactive teaching methods, ability to use active learning techniques,
ability to lead a research group.
• master modern teaching methods and tools,
• be able to use the YSU learning management system,
• provide students with modern literature and articles,
• knowledge of interactive teaching methods, ability to use active learning techniques,
ability to lead a research group.
