Data Analysis Technologies
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DepartmentFaculty of Fundamental Sciences
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Program code6121AX009
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Field of studyMathematical Sciences
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QualificationBachelor of Mathematical Sciences
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Duration4
Fun fact
Digital data is often called the “oil of the 21st century.” From your morning commute, to your latest Instagram story, to the readings on your fitness tracker—all of it is data waiting to be analyzed. Data scientists dive into these massive data lakes to find patterns, generate insights, and build smarter solutions that shape how we live, work, and connect.
We live in the age of big data—where every click, post, and search creates valuable information. Statistics is the key that helps us understand the past, make sense of the present, and even predict the future.
About
https://youtube.com/watch?v=uqOVS9XweEA%3Fsi%3DFun28ON4IHezszUG
Programme Objective
We train highly skilled data analysis specialists with a strong foundation in mathematical statistics and informatics. You’ll learn to:
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collect and interpret data
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design statistical analysis models
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apply advanced forecasting and modeling techniques
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and gain hands-on experience through individual and group projects in real-world contexts.
Core Study Modules
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Multivariate Data Analysis
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Big Data Processing Technologies
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Statistical Software (R, Python, SQL)
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Mathematical Statistics
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Sampling Methods
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Time Series Analysis (with course project)
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What will I be able to do?
• Analyze and interpret statistical data in practical contexts
• Build models for forecasting and problem-solving
• Program confidently in R and Python
• Work with databases and manage large datasets
• Apply big data processing technologies to complex real-world challenges. -
What are my career opportunities?
• Pharmaceutical companies
• Banks and insurance companies
• Private companies in data-driven sectors
• Public institutions such as the State Data Agency
Career roles include Data Analyst, Business Intelligence Specialist, Risk Analyst, or even Head of a Data Analysis Department.
Study subjects
1 Semester
obligatory
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FMSAB16131 9 credits
Differential Calculus
Module aim
To provide students with basic knowledge of mathematics, which is necessary for listening to other mathematical courses. To expose the range of applications of the differential calculus.
Module description
The course covers notions of the set of real numbers, one and several variables functions, the limit and the derivative, and applications of the derivative in engineering, economics and other fields.
Students must attend at least 51% of the lectures, at least 80% of the exercises. -
FMSAB16135 9 credits
Linear Algebra
Module aim
To make students familiar with major concepts of linear and vector algebra, with practical applications of mathematics, to teach methods of solving typical mathematical problems, to give sufficient knowledge required for understanding other subjects and for solving practical problems.
Module description
Objective of the course is to make students familiar with elements of linear algebra: matrices, determinants, such methods of solving linear equations as Cramer, Gauss, Gauss-Jordan, inverse matrix, matrix rank, compatibility of a system, elementary transformations of matrices, linear dependence of elements. Main subjects of vector algebra are delivered: basis vector co-ordinates, features of projections, operations with vectors, features and applications of scalar, vector and scalar triple products. Fundamentals of analytical geometry are analysed: different equations of a line on the plane, curves of the second degree, a line and a plane in the space, their features main problems, surfaces of the second degree.
Students must attend at least 51% of the lectures, at least 80% of the exercises. -
FMSAB24218 6 credits
Programming in Python
Module aim
Provide students with the knowledge and skills that can enable to understand the peculiarities of programming Python, to know the syntax of Python programming language, to be able to write your own programs. Provide an adequate understanding of the core Python libraries and their application possibilities, which should enable students to use them for their intended purpose.
Module description
The module explores Python programming peculiarities. Introduces Python programming language syntax, types of data structures. The module provides the basics of programming Python, an introduction to functional programming. The main Python libraries are provided, their application options are reviewed.
Students must attend at least 51% of the lectures, at least 80% of the exercises. -
FMSAB20134 3 credits
Introduction to statistical studies
Module aim
The aim is to gain knowledge about the application of elementary functions in solving classical mathematical problems, to get acquainted with complex numbers and operations with them.
Module description
The module is designed to master the basic mathematical concepts and methods that will be needed in statistical studies.
Students must attend at least 51 % of the time scheduled lectures.
one of the following
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KIUSB17101 3 credits
English Language
Module aim
To help students develop linguistic and communicative skills, acquire knowledge according to CEFR B2-C1 level in order to communicate spontaneously both in written and spoken forms on daily, cultural and professional topics.
Module description
The course covers an important aspect of academic language study relevant to all subject areas. The aim of the course is to reach a high (B2-C1) level of English to study in an academic institution. The course is aimed at the first-cycle students with B1-B2 level of English. The integrated skills course will develop students’ reading, writing, listening and speaking skills in an academic context. It will enable students to prepare assignments, write a research paper in English. Participation in at least 60% of the scheduled exercises is mandatory.
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KIUSB17105 3 credits
French Language
Module aim
To help students develop linguistic and communicative skills, acquire knowledge according to CEFR B2-C1 level in order to communicate spontaneously both in written and spoken forms on daily, cultural and professional topics.
Module description
The course covers an important aspect of academic language study relevant to all subject areas. The aim of the course is to reach a high (B2-C1) level of French to study in an academic institution. The course is aimed at the first-cycle students with B1-B2 level of French.The integrated skills course will develop students’ reading, writing, listening and speaking skills in an academic context. It will enable students to prepare assignments, write a research paper in French. Participation in at least 60% of the scheduled exercises is mandatory.
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KIUSB17103 3 credits
German Language
Module aim
To help students develop linguistic and communicative skills, acquire knowledge according to CEFR B2-C1 level in order to communicate spontaneously both in written and spoken forms on daily, cultural and professional topics.
Module description
The course covers an important aspect of academic language study relevant to all subject areas. The aim of the course is to reach a high (B2-C1) level of German to study in an academic institution.The course is aimed at the first-cycle students with B1-B2 level of German.The integrated skills course will develop students’ reading, writing, listening and speaking skills in an academic context. It will enable students to prepare assignments, write a research paper in German. Participation in at least 60% of the scheduled exercises is mandatory.
2 Semester
obligatory
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FMSAB16232 9 credits
Integral Calculus
Module aim
To provide students with basic knowledge of mathematics, which is necessary for listening to other mathematical courses. To expose the range of applications of the integral calculus.
Module description
The first part of the module sets out the basic concepts of integral calculus. The second part of the module presents the convergence tests of series of numbers and functions, Taylor’s series for functions.
Students must attend at least 51% of the lectures, at least 80% of the exercises. -
FMISB16204 6 credits
Algorithms and Data Structures
Module aim
The aim of the course is to introduce students to the data structures and their practical realization by creating the corresponding functions and classes, teaching algorithms, analyzing and evaluating them.
Module description
Concept of data structures. Linear data structures: vector, list, stack, queue, deck, heap. Hierarchical data structures: binary tree, AVL tree, Bayer tree, Red-Black tree. Memory demand and efficiency of data structures. Algorithms, complexity, asymptotic analysis. Sorting algorithms. Searching algorithms. Recursive algoritms, memory allocation. Data exchange between external and internal memory in sorting and searching algoritms.
Students must attend at least 80% of the time scheduled laboratory work. Mandatory minimum attendance of module lectures – 50%. -
FMSAB16236 6 credits
Matrix Calculation
Module aim
The purpose is to give the mathematical knowledge, which take the potential to analyse and solve the various practical problems related with linear processes and the linear analysis of the date basis as well.
Module description
In the module are included the following questions: the polynomials and their roots, linear spaces (including vector spaces), the properties of linear operators in the vector spaces, the eigenvalues and eigenvectors of the matrices, the types of matrices, the Jordan forms of matrices, the square forms of matrices, the norms of the vectors and matrices, the errors of solutions of the linear algebraic systems, the matrix functions and their application in the solving of the systems of differential equations.
Students must attend at least 51% of the lectures, at least 60% of the exercises. -
KIFSB17109 3 credits
Philosophy
Module aim
The course is intended to introduce students to the basic problems of philosophy and to provide with skills for critical thinking.
Module description
The course examines the origin of philosophy and the role of philosophy in the development of European cultural history. Course presents the topics of being, the nature of things and ideas, knowledge, the relationship between science and philosophy, the human place in cosmos, in a society and in the state. The main focus is placed upon antique philosophy and its subsequent interpretations.
Students must attend at least 60 percent of the seminars and at least half of the lectures at the scheduled times -
VVVKB17160 3 credits
Management
Module aim
To form organization management theoretical knowledge base, to develop capability to use acquired knowledge analysing situations of organizations in professional field.
Module description
During management course contains management substance, basic concepts and their interpretation. The course conveys evolution of management, identified management object and subjects, organisation elements and surroundings, administrative solutions cycle and their phases, economic, psychological, administrative management methods. There are analysed management functions: prognostication, planning, organization, accounting, control and analysis, as well as projecting of management structures and adaptation, management, horizontal and vertical communication, employee evaluation, remuneration and motivation, organisation establishment and control. Students of the first and second courses of full-time bachelor studies must attend at least 60% of exercises and at least half of the theoretical lectures according to the timetable.
one of the following
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KIUSB17123 3 credits
Speciality English Language
Module aim
To help students acquire and develop linguistic and professional communicative skills as well as relevant knowledge so that the future specialists are able to use their acquired competences and analyse information, communicate in spoken and written language in their everyday, academic and Professional situations.
Module description
The course is targeted at students’ C1 level of the English Language competences, for further development of skills gained in the course English Language for communication in both daily and professional situations. The course develops the independent user’s language skills, professional vocabulary, the correct technical and scientific language usage knowledge, abilities to analyse and summarize speciality literature, effective academic presentation skills. Participation in at least 60% of the scheduled exercises is mandatory.
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KIUSB17125 3 credits
Speciality French Language
Module aim
To help students acquire and develop linguistic and professional communicative skills as well as relevant knowledge so that the future specialists are able to use their acquired competences and analyse information, communicate in spoken and written language in their everyday, academic and Professional situations.
Module description
The course is targeted at students’ C1 level of the French Language competences, for further development of skills gained in the course French Language for communication in both daily and professional situations. The course develops the independent user’s language skills, professional vocabulary, the correct technical and scientific language usage knowledge, abilities to analyse and summarize speciality literature, effective academic presentation skills.
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KIUSB17124 3 credits
Speciality German Language
Module aim
To help students acquire and develop linguistic and professional communicative skills as well as relevant knowledge so that the future specialists are able to use their acquired competences and analyse information, communicate in spoken and written language in their everyday, academic and Professional situations.
Module description
The course is targeted at students’ C1 level of the German Language competences, for further development of skills gained in the course German Language for communication in both daily and professional situations. The course develops the independent user’s language skills, professional vocabulary, the correct technical and scientific language usage knowledge, abilities to analyse and summarize speciality literature, effective academic presentation skills.
3 Semester
obligatory
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FMSAB24391 6 credits
Discrete Mathematics
Module aim
To introduce the main characteristis and propositions of logics, algorithm theory,coding theory, combinatorics, analytic combinatorics and graph theory, be able to apply them to the solution of real practical problems.
Module description
While studing this module studens will be introdused with main characteristics of logics, theory of algorithms, coding theory, combinatorics, the princeples of analytic combinatorics graph theory elements. The students will be tought to apply this characteristics and principles to solution of the real problems.
Students must attend at least 51% of the lectures, at least 60% of the exercises and at least 60% of the laboratory work during the scheduled time. -
FMSAB16301 6 credits
Selected Topics of Analysis 1
Module aim
To provide basic knowledge about integral calculus of functions of several variables and differential calculus of functions of a complex variable.
Module description
The first part of the course presents the integral calculus of functions of several variables: multiple integrals, their properties and calculation, line integrals, their properties and calculation. The second part of the course presents the main concepts of the theory of functions of a complex variable: limit and continuity, derivative, Cauchy-Riemann equations, the concept of analytic function.
Students must attend at least 51% of the lectures, at least 80% of the exercises. -
FMSAB24379 6 credits
Statistics Software
Module aim
To introduce students to the possibilities of using the statistical software R. To enable students to successfully apply acquires knowledge in the studies of forthcoming subjects.
Module description
The module is devoted to acquire statistical computer software with the main attention devoted to the following elements: data entry, transformations and manipulation, using of descriptive statistics, presenting data in graphs.
Students must attend at least 51% of the lectures, at least 60% of the exercises. -
FMSAB16338 6 credits
Probability Theory
Module aim
To provide basic knowledge about natural phenomena of stochastic nature and their mathematical models.
Module description
The first part of the course introduces the concepts of a random event and its probability, and defines a probabilistic space. The following is the classical definition of probability, the main properties of probabilities are proved. The second part of the course is devoted to the analysis of random variable distributions. The numerical characteristics of random variables are introduced in detail. The course introduces the law of large numbers, the central limit theorem.
Students must attend at least 51% of the lectures, at least 80% of the exercises. -
VVEIB17189 3 credits
Economics
Module aim
To study economics as to acquire understanding of basic economic categories and theories. Introduce students with basic economics and possibilities to adapt them in professional studies.
Module description
During the course of Economics are studing the economic theory: the needs, resources, production, labor and material resources in the economy. There are analysing the market, supply and demand balance, elasticity as well as a company’s costs and profits differentiation and competition models. Also there are analysing the investment, business environment factors, pricing strategy and methods, as well as macroeconomic indicators, GNP calculation methods. The course analyses the fiscal and monetary policy measures, the labor market, assessment of unemployment and inflation, international economic relations, business risk and instruments of its reduction, business development.
Students must attend at least 60 % of the time scheduled exercises.
Minimum manadatory attendance of module lectures is 50 %.
one of the following
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KIFSB17128 3 credits
Ethics
Module aim
Acquaint with philosophical ethics and fundamental ethical problems and concepts. Transmit a knowledge of ethical foundations, principles and systems. Foster critical judgement and the capacity for logical, reasoned discussion. Encourage a sense of values.
Module description
Students learn about basic ethical schools and systems, fundamental issues of deontological and teleological ethic. Historical developement of ethical thought, periods such as Early Asian, Greece and Romain, medievvial, Reneissance, New Age and modernism. The main ethical issues are discussed: good and evil, principle of morality and free will, person as a goal in itself, notion of dignity, conscience, norm and morality, grounding morals in athority and discourse, notion of virtue, happiness and meaning of life and etc. Analyzed texts and philosophic al arguments os themost significant scholars of the field (Plato, Aristotle, Kant).
Students must attend at least 60 percent of the seminars and at least half of the lectures at the scheduled times -
KIFSB17127 3 credits
Logic
Module aim
Raise a culture of thinking and the ability to automate the logic of technical knowledge and they can be applied in practice of engineering.
Module description
The course covers the studies of thinking from the point of view of their structure and form (statements, concepts, reasoning and arguments). There are some elements of mathematical logic provided. Theoretical presentation is aimed at most at practical thinking problems that demand everyday training for formal logical thinking, ability to model, discuss, draw generalizations and conclusions, make decisions.
Students must attend at least 60 percent of the seminars and at least half of the lectures at the scheduled times -
KIKOB17047 3 credits
Public Communication
Module aim
The aim of the course is to introduce the theoretical and practical aspects, issues and applications of public communication.
Module description
Public Communication course aims to introduce personal branding, corporate communication, communication with clients and internal communication, the students who have chosen studies of engineering sciences, computer sciences, technology sciences, mathematics sciences. Students learn how to present themselves and their ideas, better speak in public, to make good and convincing points, to better use the internet and social media for their professional goals, also to understand cross-cultural communication. The importance of media channels, messages and communication to target audiences are also introduced in the course. Through practical tasks for personal branding, students will learn how to adopt public ethics, protocol standards. In this course an approach of learning by doing is combined with theoretical analysis and students’ self-reflection. The practical part of the course consists of active participation in discussions during different exercises, case studies as well as preparation and presentation of public speeches and presentations.
Participation in at least 60% of the scheduled exercises is mandatory. Lecture attendance is at least 50%
4 Semester
obligatory
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FMITB16437 6 credits
Database Management
Module aim
Provide the information about DBMS, introduce a comparison of the differences, advantages and disadvantages; be able to create the database, use the SQL language, write queries, create GUI.
Module description
The course is designed to familiarize students with databases and database management systems concepts. Provides information on possible actions to databases, database users are presented, their possible rights working with databases and database security. Also course introduces the graphical user interface development as well as generating reports and its presentation.
Students must attend at least 80% of the time scheduled laboratory work and at least half of the lectures at the scheduled times. -
FMSAB20439 6 credits
Mathematical Statstics
Module aim
The aim of this course is to train students in statistical analysis of real data and in interpratation of resultsand to prepare him for e tuding of econometrics and other advanced statistical courses.
Module description
The aim of this course is to introduce principles, main problems and methods of statistical data analysis. The elements of robust statistica and Bayes appoach are also encompassed. R is used for practical statistical tasks.
Students must attend at least 51% of the lectures, at least 80% of the exercises. -
FMSAB16402 6 credits
Selected Topics of Analysis 2
Module aim
To provide basic knowledge about integral calculus of functions of a complex variable, differential equations and applications in probability theory and statistics.
Module description
The first part of the course presents the integral calculus of the functions of a complex variable. The second part of the course presents the Fourier series, the Fourier transform and its application in probability theory and statistics, understanding of differential equations.
Students must attend at least 51% of the lectures, at least 80% of the exercises. -
FMSAB24488 6 credits
Numerical Methods
Module aim
To provide a sufficient understanding of major problems, definitions of numerical methods, and possibilities of application of the methods in practice, to deliver skills for solving typical problems, and to cultivate skills for solving various economical and other problems.
Module description
In the module the following subjects are delivered: interpolation of functions, interpolation by splines, numerical intergration, solution of non-linear problems, solutions of linear equation systems by direct and iterational methods, solutions of eigen-problems by numerical methods, function optimisation algorithms.
Students must attend at least 51% of the lectures, at least 80% of the exercises. -
VVFRB17404 3 credits
Personal Finance
Module aim
To introduce the students the importance of individuals’/families’ finance management.
To give for students necessary knowledge about personal finance management principles and methods, saving, investment and borrowing possibilities and instruments.Module description
Personal finance management course deals with finance and investment theories implementation for person’s (families) financial decision making, including such spheres as consumption, saving, borrowing, investment, retirement planning, insurance services, funding of real estate purchasing and tax plans.
The course covers interpretation of families budget, balance, cash flows formation and estimation, applying of these financial statement to motivate financial decisions; valuation of individual financial ratios, selection of financial instruments for achieving of set long and short term goals; examination of consumption, saving, investment and borrowing decision making, investment strategy, presentation of retirement planning strategies, methods of financial resources management in various stages of life cycles.
Students must attend at least 60 per cent of the seminars and at least half of the lectures at the scheduled times. -
KILSB19002 3 credits
Specific Purpose Language Culture
Module aim
To introduce a student with the peculiarities of the scientific style, the requirements for the terms, the principles of terms regulation, the regularities of Professional language, To teach to write and edit a scientific text.
Module description
Standard language: its functional styles and substyles. Written and spoken language. Public and non-public language. Special and professional language. Terms as the basis of a professional language. Structural characteristics and parameters of a scientific text. Composition of a scientific text. Linguistic analysis of final works for the Bachelor`s and Master`s Degree. Participation in at least 60% of the scheduled exercises is mandatory.
The academic style and its place in the system of functional styles is analyzed. The differences of spoken and written language, the public and non-public language features are discussed. A detailed analysis of the terms concept, types, requirements, structure, terminology management techniques is presented. The focus on the analysis of scientific language expression patterns and disadvantages of scientific text composition features.
5 Semester
obligatory
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FMSAB19531 6 credits
Theory of Random Processes
Module aim
To acquaint with the main classes of random processes and methods applied in the theory of random processes. To deepen and expand the acquired knowledge of probability theory.
Module description
This course introduces the concept of random process, the basic classes of random processes and methods applied in the theory of random processes.
Students must attend at least 80 % of the time scheduled practical lectures. -
FMSAB21586 6 credits
Optimization Methods
Module aim
This course aims to provide students the fundamental concepts of mathematical programming and develop their ability in applying basic techniques of solving optimization problems.
Module description
This course is an introduction to linear optimization, with an emphasis on techniques for the solution and analysis of deterministic linear models. The topics covered include: mathematical properties of linear programming models, the geometry of linear optimization,the simplex method, duality theory, sensitivity analysis, integer programming, transportation problem and matrix games.
Students must attend at least 80 % of the time scheduled practical lectures. -
FMSAB16542 6 credits
Regression Analysis
Module aim
The aim of this course is to introduce models, principals and methods of regression analysis and related model, their applications and interprataion in econometric studies and to teach students to perform with computers statistical analysis of real economic data.
Module description
The basis of this introductory econmometric course is regression analysis and related models: dispersion and factor analysis. The aim of the course is to introduce principals of econometric analysis, main concepts and methods of regresion, dispersion and factor analysis, to teach students to apply this methods in real studies and correctly to interpret the results.
Students must attend at least 80 % of the time scheduled practical lectures and at least 80 % laboratory works. -
FMSAB20532 6 credits
Computational Statistics
Module aim
The aim of this course is to train students in statistical analysis of real data and in interpratation of resultsand to prepare him for e tuding of econometrics and other advanced statistical courses.
Module description
The aim of this course is to introduce principles, main problems and methods of statistical data analysis. The elements of robust statistica and Bayes appoach are also encompassed. R is used for practical statistical tasks.
Students must attend at least 80 % of the time scheduled practical lectures. -
FMSAB24534 3 credits
Introduction to Graph Theory
Module aim
This course aim is to provide students with the fundamental concepts of graph theory and develop their ability to apply basic techniques and algorithms of graph theory into practice.
Module description
During the course students are introduced with the main concepts of graph theory, metric characteristics, gets acquainted with specific graph theory tasks and exercises, possible solution algorithms and how to solve these problems using statistical software packages.
Students must attend at least 80 % of the time scheduled practical lectures.
Free choice
6 Semester
obligatory
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FMSAB21641 9 credits
Time Series Analysis (with course project)
Module aim
The aim of this course is to introduce the main time šeries models and to consider their application in practice.
Module description
The main conceptions in creating time series statistical models are presented in this course. The questions of a model identification, fitting the models parameters, model diagnostic and forecasting are considered. Besides theoretical knowledge students have to solve tasks on the black board and using the special statistical program package for full statistical analysis.
Students must attend at least 80 % of the time scheduled practical lectures. -
FMSAB23694 6 credits
Multivariate Data Analysis
Module aim
The purpose of this course is to introduce various topics in multivariate analysis and to provide some practical experience in their applications and interpretation.
Module description
This course introduces the basic concepts of multivariate statistics, and provides an overview of methods for the statistical data analysis. The course content includes theory of the multivariate data visualisation, principal component analysis, factor analysis, multidimensional scaling and correspondence analysis. All methods will be illustrated with the real data sets, using the open source statistical software R.
Students must attend at least 80 % of the time scheduled practical lectures. -
FMMMB21602 6 credits
Big Data
Module aim
The goal is to introduce the basic numerical methods and to learn how to apply these methods for solution of specific problems.
Module description
In this course students learn the concepts of computer arithmetic and stability of numerical algorithms, numerical methods for solution of nonlinear equations and systems of equations, direct and iterative methods for solution of linear systems of equations, interpolation and approximation, numerical methods for solution of eigenvalue and eigenfunction problems, optimization methods, and numerical integration methods.
Students must attend at least 60% of the time scheduled practical works. -
FMSAB16674 6 credits
Data Classification Methods
Module aim
The aim of this course is to make students familiar with major concepts of classification analysis, to understanding the mathematics behind classification methods, to provide practical experience in solving data classification tasks.
Module description
Classification is one of the main tasks in statistical data analysis in biology, medicine, engineering and other fields. In this course, students are introduced to the basic principles of data classification, the most common types of tasks and methods of solving them: cluster analysis, discriminant analysis, etc.
Students must attend at least 80 % of the time scheduled practical lectures and at least 80 % laboratory works.
Free choice
7 Semester
obligatory
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FMSAB24798 6 credits
Statistical Analysis of Discrete Structures
Module aim
This course aims to provide students the fundamental concepts of the theory of the general linear models and to provide some practical experience in their applications and interpretation.
Module description
Discrete data are collected in social, biomedical and biological sciences as well as in linguistics, genetics, engineering, and education. The statistical inference for discrete data involves special methods that differ from those for continuous random variables. This course will focus on the theory and application of generalized linear models. The course content includes contingency tables and association between categorical variables, the exponential family of distributions, generalized linear models, logistic regression, and loglinear models. All methods will be illustrated with real data sets, using the open source statistical software R.
Students must attend at least 80 % of the time scheduled practical lectures. -
FMSAB23752 6 credits
Sampling Methods
Module aim
To present the main knowledge on sampling theory and to give possibility to apply them to the data of practical surveys.To teach to design the survey taking into account the real conditions, for complex sampling design to estimate parameters of finite population end errors of the estimates.
Module description
The module designed to imbibe main sampling designes used for finite populations surveys, methods of estimation of the parameters and measures of accuracy of the estimators, to make acquaintance of the methods of adjustment to non-response and computer software for these methods. Theoretical results are illustrated with examples of practical surveys, which are carried out by public opinion and market reserachers, oficial statistics.
Students must attend at least 80 % of the time scheduled practical lectures. -
FMITB23701 6 credits
Introduction to Neural Networks
Module aim
Familiarization with neural networks and their application.
Module description
Fundamentals of neural networks: an artificial neuron, an activation function, weights, bias, layers. Neural network architectures. Learning process. Practical applications of neural networks.
Students must attend at least 80% of the time scheduled laboratory work. -
VVTEB23701 3 credits
Copyright Law
Module aim
To provide students with the comprehensive knowledge on copyrights and related rights, as one of the types of intellectual property while dealing with the legal framework in Lithuania and other countries, to acquire skills to analyze the theoretical and practical problems in the copyright Law and to expand students’ capacity for self-absorption in this field
Module description
The module involves the exploration of copyright rights and related rights among other types of intellectual properties, development of Copyright Law and its sources in Lithuania and other countries, the peculiarities of different types of copyrights and related rights, their subjects, objects, protection and implementation of copyrights.
Students must attend at least 60 % of the time scheduled practical exercises (practical work). -
FMSAB23780 3 credits
Final Work 1
Module aim
Objectives – the formulation of the topic for final work, literature overview, study and analysis of the expected results, the perception and understanding of problematic of the final work topic.
Module description
The study of literature on the topic of final work, analysis, and preparation of literature overview. The development of mathematical model, the mastering of the suitable software for final work.
one of the following
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FMSAB23770 6 credits
Acturial Mathematics
Module aim
Course objective – to acquaint students with the mathematical theory of interest and to teach to use them in practical tasks. To get acquainted with the life insurance mathematical models.
Module description
Students are introduced to the financial calculations, life insurance mathematical basis.
Students must attend at least 80 % of the time scheduled practical lectures. -
FMSAB24730 6 credits
Introduction to Bayesian statistics
Module aim
To provide a sufficient understanding of major problems in Bayesian statistics, by giving the main differences between Bayesian and classical statistics, to teach to construct a posteriori distributions of known parameters and to apply a posteriori distributions in the solution of practical problems.
Module description
In this module, the main concepts of Bayesian analysis are discussed: probability, a priori distribution, a posteriori distribution. Statistical models based on a priori conjugate distributions are analyzed, with the help of which a posteriori distributions of known parameters are obtained: Bayesian inference for Binomial, Poisson, Normal variables, Bayesian inference for simple linear regression and robust Bayesen methods.
Students must attend at least 80 % of the time scheduled practical lectures. -
FMMMB23701 6 credits
Basic Mathematical Modelling
Module aim
To give fundamentals of basic methods of mathematical modelling.
Module description
Basic methods of mathematical modelling. Mathematical models described by scalar first order ODE. Second order ODE. Enzyme kinetics, interacting populations. Difference equations in mathematical modelling.
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FMSAB23787 6 credits
Reliability Theory
Module aim
To present some knowledge of applications of the methods of the probability theory and mathematical statistics in analysis of reliability of the separate elements and their systems.
Module description
In the course, the knowledge on the reliability of the separate elements and their systems, analysis of reliability and estimation of reliability parameters is given. There are discussed the reliability characteristics, reliability of the unreplaceable and replaceable elements and the statistical methods in reliability analysis. Then attention is given to the reliability hypothesis and the methods of the selective reliability control.
Students must attend at least 80 % of the time scheduled practical lectures.
8 Semester
obligatory
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FMSAB23882 15 credits
Final Work
Module aim
Objectives – to fully complete the final work and submit a complete description of the final work.
Module description
Fully carried out theoretical and practical parts of the final work, the complete description of the final work, corresponding to the final work-processing requirements, is presented. Emphasis on theoretical and practical value of the final work.
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FMSAB23885 15 credits
Professional Internship
Module aim
To make acquaintance with the methods, models and software for statistical data analysis used in the enterprise.
Module description
The student during the proction practice has to make acquaitnce with the structure of the enterprise, its activity processes, data bases and their management system. The student has to perform the practical work related to the quantitative data available to build a model or to apply the known model for the solution of the problem received, to choose th computer software and to present an accurate task report. If it is possible the student may collect data for the final theses. The duration of the production practice – 8 weeks. The students prepares an individual report on the practice.
Statistics
| Metric | Value |
|---|---|
| Enrolled students | 15 |
| Enrolled to FT | 11 |
| Min FT grade | 7.53 |