Educational programs in Mathematical Programming introduce students to the Python programming language, with which they explore and study practical mathematical problems. Python is one of the most powerful and versatile programming languages, it is increasingly used by engineers, scientists, as well as banks and financial institutions to solve their computing tasks. The Mathematical Programming degree improves the experimental aspect of mathematics and uses Python-based computational tools to better understand problems, discover mathematical models and relationships, and use visualization techniques to identify mathematical structures.

The academic program provides students with knowledge of the basic theoretical and algorithmic methods of mathematical programming for solving optimization problems and decision-making tools; is able to analyze the optimization problem and develop an appropriate mathematical model for its solution. The degree in Mathematical programming includes an illustration of real-world applications and laboratory experiments showing how to implement an algorithm based on a mathematical programming model and how to use the most important solutions available.

This guide focuses on optimization problems that arise when making decisions and determining accurate mathematical models and algorithms for solving them. The mathematical theory on which these methods are based is developed by studying theorems. The main areas of education will be:

Introduction to emerging optimization problems in decision-making and mathematical programming;

• Convex programming, linear programming, simple algorithm, duality theory;

• Correct linear programming, sub deterministic and deterministic algorithm, classical combinatorial optimization problems, relaxation, computational complexity;

• Exponential volume models, column generation, constraint separation;

• Graphical tasks, examples of real applications, software optimization tools.

Specialization of mathematics with computer science involves a combination of mathematics and computer science. The textbook on mathematical programming is intended for students who want to pursue a career in IT-related fields where a good mathematical education is required. Students can build their careers in the following fields: information research analyst, software developer, operational research analyst, database administrator, marketing research analyst, cryptanalyst, data analyst, applied scientist, professor of mathematics or computer science. Fields of study may include: computer science, data structure and algorithm, analysis, software design and development, operating systems and systems, programming, computing, applied statistics, higher mathematics, discrete mathematics, linear algebra.

Academic programs in mathematical programming allow students to develop a deep understanding of how the subject is related to other areas of human research by focusing on a course that focuses on the areas in which mathematics and computer science are most relevant to each other, with an emphasis on the bridges that connect mathematics and computer science focus between theory and practice. This gives potential computer scientists the opportunity to gain a deeper understanding of the mathematical foundations of their field and to become familiar with the mathematics of applications in which computers can solve problems that would otherwise be unsolvable. It also gives mathematicians access to a practical understanding of how computers are used and a deeper understanding of the limitations of using computers in their particular field.