Цель: The Master's program in Computational Sciences and Statistics is aimed at training highly qualified specialists in the field of computational sciences, methods of stochastic computing, decision-making methods, high-performance computing, computational grids, and machine learning.
A graduate of this educational program can also carry out research and teaching activities in research institutes and universities.
Предметы на ЕНТ:
Mathematical analysis и Differential equations
Educational program
The Master's program in Computational Sciences and Statistics is aimed at training highly qualified specialists in the field of computational sciences, methods of stochastic computing, decision-making methods, high-performance computing, computational grids, and machine learning.
A graduate of this educational program can also carry out research and teaching activities in research institutes and universities.
ON 1 Develop and use algorithms for computational research and experiments using modern effective methods of computational mathematics
ON 2 Develop methods and algorithms for computational mathematics based on the approximation of differential equations by methods of finite differences, volumes or elements
ON 3 Conduct a fundamental analysis of computational methods and difference schemes for convergence and correctness, including in the case of high-performance algorithms using elements of mathematical logic and the theory of computability
ON 4 Solve computational problems with complex geometry of regions by building and using correct structured, curvilinear, unstructured computational grids
ON 5 Use deep learning-based data mining techniques, reinforcement learning to adapt the computational algorithm to efficiently predict outcomes
ON 6 Conduct classes in mathematical disciplines offline and online based on innovative technologies, developing methodological recommendations for independent student work, laboratory, practical, lecture courses, textbooks, teaching aids, educational work plans, etc.
ON 7 Develop parallel computing algorithms for engineering problems and implement them in high-performance systems, develop quantum computing algorithms.
ON 8 Develop and conduct computational simulations of probabilistic processes from various industries using stochastic analysis methods and stochastic differential equations
ON 9 Use the methods of mathematical statistics in various areas of the economy and production, on real data for the selection of parameters, adaptation and testing of computing systems based on real experiments
ON 10 Conduct independent scientific research, solving modern urgent problems, publishing results in rating journals and speaking at conferences
Master's degree educational programs
Persons entering the master’s degree or residency:
when applying to organizations of university and postgraduate education:
1) an application addressed to the head of the organization of higher and postgraduate education in any form;
2) document on higher education (original);
3) certificate of completion of the internship (for admission to residency);
4) identity document (required for personal identification);
5) six photographs 3x4 centimeters in size;
6) a medical certificate in the f
Curriculum
СЕМЕСТР 1
History and philosophy of science-3 ECTS
Pedagogy of Higher education-5 ECTS
Stochastic analysis and applications-5 ECTS
Stochastic approximation and control-5 ECTS
Analysis of the Lattice Boltzmann Equation-5 ECTS
Lattice Boltzmann method for single-phase and multiphase flows-5 ECTS
High performance computing-5 ECTS
Quantum computing algorithms-5 ECTS
Research Seminar-1 ECTS
Dissertation Writing-1 ECTS
СЕМЕСТР 2
Foreign Language (professional)-5 ECTS
Psychology of Management-3 ECTS
Pedagogical-4 ECTS
Stochastic differential equations and their applications-5 ECTS
Numerical Implementation of the Lattice Boltzmann Method-5 ECTS
Organization and Planning of Scientific Research (in English)-5 ECTS
Unstructured grid generation methods-5 ECTS
Research Seminar-1 ECTS
Dissertation Writing-2 ECTS
СЕМЕСТР 3
Computational Methods for Solving Inverse Problems-5 ECTS
Computational methods for solving hydrodynamic problems in areas with complex geometry-5 ECTS
Research-4 ECTS
Markov Decision Processes-5 ECTS
Nonparametric Statistics-5 ECTS
Factor Analysis-5 ECTS
Deep learning-5 ECTS
Big Data analytics-5 ECTS
Distributed systems and data processing in real time-5 ECTS
Dissertation Writing-1 ECTS
СЕМЕСТР 4
Final Attestation-8 ECTS
Publication in the Proceedings of International Conferences-4 ECTS
Scientific Internship-3 ECTS
Dissertation Writing-10 ECTS
Research Seminar-1 ECTS
Research-4 ECTS
Employment
Master's student can work in research and educational institutions, analytical and consulting companies, industrial enterprises, IT companies, financial institutions and government organizations. They can hold positions as analysts, statistics specialists, research and development specialists, teachers, project managers, researchers, as well as consultants in their fields. Master's student often participate in complex scientific and applied projects that require in-depth knowledge and skills in analytical thinking, modeling and data management.
Contacts
Address: 71/23 al-Farabi Ave, Almaty, Faculty of Mechanics and Mathematics, 5th floor, room 506.
Phone: 8 (727) 221-15-73
Documents of EP
23123123
APPLICATION 1_7M05408-COMPUTATIONAL SCIENCES AND STATISTICS.pdf
