System Analysis
Faculty of Computer Science and Cybernetics
Name
System Analysis
Program code
124
Qualification awarded
Bachelor of Systems Analysis
Length of programme
4 years
Number of credits
240
level of qualification according to the National Qualification Framework and the European Qualifications Framework
6
Qualification level
First (Bachelor)
Discipline
Information technologies
Speciality
KnowledgeField EN
Specific admission requirements
Certificate of complete general secondary education
Specific arrangements for recognition of prior learning
Qualification requirements and regulations, including graduation requirements
The professional qualification "Information Technology Specialist" is assigned on the basis of:
1. Successful mastering of the competencies of the block of disciplines of free choice of the student with grades not lower than 75 points;
2. Passing of all practices, which are provided by the curriculum, with grades not lower than 75 points;
3. Protection of the qualification work of a bachelor (by professional qualification) with a score of at least 75 points
Programme learning outcomes
Program learning outcomes
PR01. Know and be able to apply in practice differential and integral calculus, Fourier series and integrals, analytic geometry, linear algebra and vector analysis, functional analysis and discrete mathematics to the extent necessary to solve typical problems of systems analysis.
PR02. Be able to use standard schemes for solving combinatorial and logical problems formulated in natural language, use classical algorithms to check the properties and classification of objects, sets, relations, graphs, groups, rings, lattices, Boolean functions, etc.
PR03. Be able to determine the probability distributions of stochastic indicators and factors influencing the characteristics of the studied processes, investigate the properties and find the characteristics of multidimensional random vectors and use them to solve applied problems, formalize stochastic indicators and factors in the form of random variables, vectors, processes.
PR04. Know and be able to apply basic methods of qualitative analysis and integration of ordinary differential equations and systems, differential equations in partial derivatives, including equations of mathematical physics.
PR05. Know the basics of the theory of metric spaces, Lebesgue theory of measure and integral, the theory of bounded linear operators in Banach and Hilbert spaces, apply techniques and methods of functional analysis to solve problems of control of complex processes under uncertainty.
PR06. Know and be able to apply the basic methods of setting and solving problems of systems analysis in conditions of uncertainty of goals, external conditions and conflicts.
see further http://applstat.univ.kiev.ua/ukr/docs/opp/opp_2019.pdf
Form of study
Full-time form
Examination regulations and grading scale
Final certification is carried out in the form of defense of the bachelor's thesis (diploma project or work) and a comprehensive exam in applied mathematics and ends with the issuance of a standard document on awarding him a bachelor's degree with the qualification: Bachelor of Systems Analysis.
During the qualifying exam, the program learning outcomes PR01-PR12 are checked. The qualifying exam is conducted orally and consists of theoretical questions and tasks.
The professional qualification "System Analysis Specialist" is assigned by a separate decision of the examination commission on the basis of: 1. Successful mastering of the competencies of the block of disciplines of free choice of the student with grades not less than 75 points; 2. Passing of all practices, which are provided by the curriculum, with grades not lower than 75 points; 3. Protection of the qualification work of a bachelor (by professional qualification) with a score of at least 75 points.
Оbligatory or optional mobility windows (if applicable)
Work placement
Work-based learning
Director of the course
Mykhailo
Mykhailovich
Sharapov
Applied Statistics
Faculty of Computer Science and Cybernetics
Faculty of Computer Science and Cybernetics
Occupational profiles of graduates
Professional activities in positions related to the development of systems analysis in the field of information technology and / or solving complex organizational and technical problems that are interdisciplinary in nature, using the principles of general systems theory and methods of systems analysis.
Access to further studies
Opportunities for continuing education at the second (master's) level of higher education
Subjects
As part of the curriculum, students study the following disciplines
Introduction to university studies
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Equations of mathematical physics
Code: ДВВ.11,
Ukrainian and foreign culture
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Philosophy
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Socio-political studies
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Selected sections of labor law
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Foreign Language
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Scientific image of the world
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Ecological and economic processes and their modeling
Code: ННД.08,
Differential equations
Code: ННД.24,
Algebra and Geometry
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Discrete mathematics
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Mathematical analysis
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Mathematical analysis 2
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Programming
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Architecture of computer systems
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Decision making theory
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Systems analysis
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Data analysis
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Conflict-controlled systems
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Actuarial mathematics
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Production practice
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Preparation of final qualifying work
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Introduction to operations research
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Differential equations
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Computer networks
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Probability theory and mathematical statistics
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System optimization
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Numerical Methods
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Algorithm theory and mathematical logic
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Management information technologies
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Basics of database design
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Operating Systems
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Mathematical demography and modeling of random processes. Module 1. Mathematical demography
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Mathematical demography and modeling of random processes. Module 2. Modeling of random processes
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Theory of queuing. Module 1. Module 2.
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Theory of evaluation of systems in conditions of uncertainty
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Symmetric cryptography
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Decomposing methods of discrete optimization
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Mathematical methods of measuring economic risk
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Mathematical models of pension and health insurance
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Asymmetric cryptography and public key cryptosystems
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Module 1. Probabilistic bases of the simulation method
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Module 2. Assessment methods in applied research
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Module 3. Modern problems of discrete optimization
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Programming paradigms
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