Bachelor of Science in Mathematics
The Bachelor of Science Program in Mathematics is a 240 ECTS program and is to be completed in 8 regular semesters. The program is designed to train students in the theory of mathematics and to develop mathematical skills and mastery, used in the modern applications of mathematics in science and engineering. Through specialized courses as part of mathematics elective and technical elective requirements, students will have the opportunity to deepen and broaden their mathematical foundations and skills, which will make them more competitive in the mathematics-related job market and/or will prepare them for graduate studies in the area of pure and applied mathematics or statistics. Flexibility in selecting non-mathematics electives will also allow students to complete a minor in a different discipline.

Requirements for the completion of study consist of four parts:

  1. Mathematics requirement, at least 102 ECTS, comprising of

      Core courses (74 ECTS):

      Elective courses (at least 28 ECTS):

  • 300- and 400-level MATH courses with at least 24 ECTS at the 400 level
  1. Natural Science requirement, at least 34 ECTS, with three compulsory courses:
  • PHYS 161 Physics I for Scientists and Engineers with Laboratory
  • PHYS 162 Physics II for Scientists and Engineers with Laboratory
  • PHYS 270 Computational Physics with Laboratory
  1. Computer Science requirement, at least 16 ECTS, with compulsory courses
  • CSCI 151 Programming for Scientists and Engineers
  • CSCI 152 Performance and Data Structures
  1. Humanity-Social Science requirement, at least 42 ECTS, with compulsory components
  • HST 100 History of Kazakhstan (compulsory)
  • 2 Kazakh Language/Literature courses


For a sample of the study plan, click link.

Descriptions of courses can be found in this link.

For inquiries, please contact the Director of Undergraduate Program.

For inquiries concerning MSc Program, please contact the Graduate Program Director.



MATH 499 Graduation Project

Short description

MATH 499 Graduation Project is a 6-ECTS elective, which is counted towards the mathematics core elective credit requirement. The goal of the course is to engage the student in original thinking and independent work towards the creation of a capstone thesis under the supervision of an experienced faculty.


The timeline for the course is the following:

  • Fall Semester Week 3: choice of a supervisor among the math faculty.
  • Spring Semester Week 1: assessment of the student’s preparation by supervisor.
  • Spring Semester Week -4: composition of the thesis committee (choice of second reader).
  • Spring Semester Week -2: public defense.
  • Spring Semester Week -1: submission of revised thesis.


The grade for the course, decided by majority in the thesis committee (supervisor, second reader and course coordinator) is Pass/Fail.



  • Students can withdraw at any time or can be withdrawn by their supervisor in case of inadequate preparation or work.
  • It is essential that students contact a supervisor early in the fall semester, even if the course runs formally only in the spring semester.

Capstone Projects (2018-19)

  1. Low rank approximation of matrices for generating pmi  (Zhenisbek Assylbekov and Thomas Mach)
  2. Hirota equation and the wigner transform (Alejandro J. Castro Castilla)
  3. Well-posedness of nlse and mkdv equations  (Alejandro J. Castro Castilla)
  4. Hirota equation with dissipative and pumping terms (Alejandro J. Castro Castilla)
  5. A lower bound for double base expansions  (Francesco Sica)
  6. De factorisatione numerorum  (Francesco Sica)
  7. Exactly solvable multi-species stochastic particle models  (Eunghyun Lee)
  8. Analytic solutions of partial differential equations  (Daniel Oliveira Da Silva)
  9. Spectral geometry of partial differential equations and applications (Durvudkhan Suragan)
  10. Approximations of periodic solutions to problems in micro-electro-mechanical systems (Piotr Skrzypacz)
  11. Discontinuous galerkin method for nonlinear diffusion-convection problems  (Piotr Skrzypacz)
  12. Solving 1d transmission problems by finite elements (Piotr Skrzypacz)
  13. The robust finite element discretizations for dead-core problems (Piotr Skrzypacz)
  14. Differential equations in micro-electrico-mechanical systems  (Piotr Skrzypacz)
  15. Asymptotic behavior of epidemic models (Ardak Kashkynbayev)
  1. A toy model for nonlinear black-scholes equations (D. da Silva).
  2. Convergence analysis of retarded fuzzy neural networks (A. Kashkynbayev).
  3. Functional Analysis (E. Lee).
  4. Mathematical Concepts for Quantum Mechanics (E. Lee).
  5. Stochastic Calculus (E. Lee).
  6. The core of eiscor (T. Mach).
  7. Matrix polynomials in Chebyshev basis (T. Mach).
  8. Basic model of storm water and snow melt events (T. Mach).
  9. Searching for generalizations of Pac-Man conditions (R. Takhanov).

We have  11 capstone project reports from 2016 year and 4 from 2015 in the  NU repository which can be found in:


Careers in Mathematical Sciences