The goal of the BSc in Mathematical and Computer Modeling education program is to provide students with a strong foundation in mathematics and computer science, as well as the tools and techniques needed to apply these disciplines to real-world problems. Students take courses in calculus, linear algebra, probability and statistics, discrete mathematics, and computer programming. They also learn about modeling techniques such as simulation, optimization, and data analysis, and how to apply these methods to problems in fields such as finance, engineering, biology, and social sciences. 

The program aims to prepare students for careers in a variety of fields, including data analysis, financial modeling, computer science, and operations research. 

Graduates of the program may also choose to pursue further education in graduate or professional programs in areas such as mathematics, computer science, or business. The program is designed to provide students with a strong quantitative foundation and the ability to apply their knowledge to real-world problems, preparing them for success in a rapidly evolving technological landscape. 

• Apply the underlying unifying structures of mathematics (i.e. matrices, sets, relations and functions, logical structure, groups, fields, graphs, etc.) and the relationships among them on paper and oral exams based on theoretical questions.
• Demonstrate logical skills in programming in a variety of languages (i.e. R, Python, MATLAB, etc.) achieved by laboratory works and exams based on problem-solving.
• Reveal deep knowledge of differential equations by solving applied problems.
• Design different types of mathematical models and simulations including dynamical systems, statistical models, differential equations, and game theoretic models by learning fundamental mathematical courses (Calculus, Ordinary differential equations, Numerical Methods, Statistics, etc.) and practical courses on simulations.
• Apply methods of mathematical and computer modeling for solving scientific, applied, production, and technological problems by using professional software, computer graphics, visualization, and developing their own software packages.
• Show basic knowledge in Financial Mathematics, Applications of Number Theory, Data management, and analysis by learning elective courses.
• Analyze collected information and present the research results achieved through work on individual and group projects.
• The program encourages students to develop an understanding of government operations, market dynamics, institutional frameworks, societal relations, major ethical theories, and problems. Moreover, they will have the opportunity to demonstrate fluency in multiple languages through the study of non-area subjects such as economics, sociology, philosophy, Russian/Kazakh language, Turkish language, and more.

Graduates with a degree in Mathematical and Computer Modeling have a wide range of career opportunities across various industries. Here are some potential career choices:

• Data Science and Analytics: Mathematical and computer modeling skills are in high demand in the field of data science. Companies and organizations rely on data analysis to make informed decisions and gain insights into their operations. Professionals who can apply mathematical techniques, statistical modeling, and machine learning algorithms to large datasets are highly sought after.
• Financial Services: The finance industry heavily relies on mathematical models for risk assessment, asset valuation, portfolio optimization, and algorithmic trading. Skills in mathematical modeling and computer programming are essential for roles such as quantitative analysts, financial engineers, and data scientists in finance.
• Engineering and Manufacturing: Mathematical modeling is crucial in engineering disciplines such as civil engineering, mechanical engineering, and electrical engineering. Computer modeling is used to design and simulate complex systems, optimize processes, and analyze structural integrity. Skills in mathematical modeling and computer-aided design are valuable in these fields.
• Research and Academia: The combination of mathematics and computer modeling is essential in scientific research and academia. Researchers in fields such as physics, chemistry, biology, and environmental sciences often use mathematical models to analyze experimental data, simulate complex phenomena, and develop theories. Computational modeling and simulation are also prevalent in academic research.
• Government and Public Policy: Mathematical and computer models play a crucial role in informing public policy decisions. Government agencies and research institutes often employ experts in mathematical modeling to analyze social, economic, and environmental data, assess policy outcomes, and make recommendations.
• Consulting and Technology: Consulting firms and technology companies often require professionals with expertise in mathematical modeling and computer simulation. These skills are useful for developing models, conducting simulations, and providing data-driven solutions to clients’ problems in various industries.

Moreover, graduates can continue their education in MSc and PhD programs.