Master of Science in Mathematical Modelling
The Master of Science in Mathematical Modelling is a postgraduate programme that prepares professionals for advanced practice in mathematical modelling, computational mathematics, and data-driven decision-making. The programme combines mathematical theory with computational methods, statistics, and applications across science, engineering, and industry.
Core areas include mathematical modelling, computational methods, differential equations, stochastic modelling, optimisation, statistical modelling, numerical methods, data analysis, research methods, and thesis. Students engage with both theoretical and practical work through coursework, computational projects, and research.
The programme is offered by Taita Taveta University through the School of Science and Informatics. TTU is a public university offering the programme over two academic years through full-time mode of study.
Students develop competencies in mathematical modelling, computational methods, data analysis, optimisation, and stochastic processes. The programme includes coursework, examinations, computational projects, and a supervised research thesis, preparing graduates to address complex modelling challenges in science, industry, and research.
TTU charges approximately KES 155,750/year for science-based masters programmes. Entry requires a Bachelor's degree with at least Upper Second Class Honours in Mathematics, Statistics, Engineering, Economics, or related quantitative fields from a recognised institution.
Graduates pursue careers as data scientists, quantitative analysts, operations research analysts, mathematical modellers, research scientists, and lecturers in mathematics across research institutions, government agencies, financial institutions, technology firms, and universities.
Skills Required
- Mathematical Modelling and Simulation
- Computational Methods and Numerical Analysis
- Differential Equations and Dynamical Systems
- Stochastic Modelling and Processes
- Optimisation Techniques
- Statistical Modelling and Data Analysis
- Programming for Mathematical Computing
- Research Methods in Mathematics
- Data-Driven Decision Making
- Academic Writing and Thesis Research
Key Subjects
- Mathematical Modelling
- Computational Methods
- Differential Equations
- Stochastic Modelling
- Optimisation Techniques
- Statistical Modelling
- Numerical Analysis
- Data Analysis and Visualisation
- Research Methods in Mathematics
- Thesis Research
Certifications
- SIAM Professional Membership
- AMU Professional Membership
Specializations
Computational Mathematics
Focuses on computational mathematics, covering methods, algorithms, computing, simulation, and managing computational mathematics.
Stochastic Modelling
Examines stochastic modelling, covering processes, probability, randomness, simulation, and managing stochastic models.
Optimisation
Covers optimisation, covering techniques, linear, nonlinear, integer, and managing optimisation.
Biomathematical Modelling
Focuses on biomathematical modelling, covering biology, systems, ecology, population, and modelling biological systems.
Data Science and Analytics
Examines data science and analytics, covering data, statistics, analysis, visualisation, and managing data science.
Financial Modelling
Covers financial modelling, covering finance, markets, risk, pricing, and modelling financial systems.
- Duration
- 2 years
- Public, up to
- Ksh 155,750
- Private, up to
- Ksh 295,500
- Job market
- Moderate
The programme
What you study, how long it takes, and how it is delivered.
Practicalities
- Study mode
- Full-time
- Attachment
- 0 months
- Average class
- 15 students
- Award
- Masters
What you study
10 subjects- Mathematical Modelling
- Computational Methods
- Differential Equations
- Stochastic Modelling
- Optimisation Techniques
- Statistical Modelling
- Numerical Analysis
- Data Analysis and Visualisation
- Research Methods in Mathematics
- Thesis Research
Modules
12 in the programmeMathematical Modelling Foundations
Year 1Semester 13 creditsCore
Examines formulation, analysis, simulation, validation, and building mathematical models.
Computational Methods
Year 1Semester 13 creditsCore
Covers algorithms, programming, computing, simulation, and managing computational mathematics.
Differential Equations and Dynamical Systems
Year 1Semester 13 creditsCore
Examines ODEs, PDEs, dynamical systems, stability, and solving differential equations.
Research Methods in Mathematics
Year 1Semester 13 creditsCore
Covers research design, data collection, analysis, methods, and conducting research, preparing students for their thesis.
Stochastic Modelling and Processes
Year 1Semester 23 creditsCore
Examines processes, probability, randomness, simulation, and managing stochastic models.
Optimisation Techniques
Year 1Semester 23 creditsCore
Covers techniques, linear, nonlinear, integer, and managing optimisation.
Statistical Modelling and Data Analysis
Year 1Semester 23 creditsCore
Examines statistics, models, inference, analysis, and managing statistical models.
Numerical Analysis
Year 1Semester 23 creditsCore
Covers methods, errors, convergence, stability, and managing numerical methods.
Biomathematical Modelling
Year 2Semester 13 creditsCore
Examines biology, systems, ecology, population, and modelling biological systems.
Financial Modelling
Year 2Semester 13 creditsCore
Covers finance, markets, risk, pricing, and modelling financial systems.
Data Science and Visualisation
Year 2Semester 13 creditsCore
Examines data, statistics, visualisation, interpretation, and managing data science.
Research Thesis
Year 2Semester 29 creditsCore
Original supervised research thesis on a mathematical modelling topic, demonstrating mastery of research methods and mathematical modelling knowledge, assessed through written submission and oral defence.
Specialisations
Computational Mathematics
Focuses on computational mathematics, covering methods, algorithms, computing, simulation, and managing computational mathematics.
Stochastic Modelling
Examines stochastic modelling, covering processes, probability, randomness, simulation, and managing stochastic models.
Optimisation
Covers optimisation, covering techniques, linear, nonlinear, integer, and managing optimisation.
Biomathematical Modelling
Focuses on biomathematical modelling, covering biology, systems, ecology, population, and modelling biological systems.
Data Science and Analytics
Examines data science and analytics, covering data, statistics, analysis, visualisation, and managing data science.
Financial Modelling
Covers financial modelling, covering finance, markets, risk, pricing, and modelling financial systems.
A day as a student
A typical day during the MSc in Mathematical Modelling programme combines lectures, computational labs, project work, seminars, and independent study. Sessions cover mathematical modelling, computational methods, differential equations, stochastic modelling, and optimisation. Mathematical modelling sessions examine formulation, analysis, simulation, validation, and building mathematical models. Computational methods sessions cover algorithms, programming, computing, simulation, and managing computational mathematics. Differential equations sessions cover ODEs, PDEs, dynamical systems, stability, and solving differential equations. Stochastic modelling sessions cover processes, probability, randomness, simulation, and managing stochastic models. Optimisation sessions cover techniques, linear, nonlinear, integer, and managing optimisation. Statistical modelling sessions cover statistics, models, inference, analysis, and managing statistical models. Numerical analysis sessions cover methods, errors, convergence, stability, and managing numerical methods. Data analysis sessions cover data, statistics, visualisation, interpretation, and managing data analysis. Research methods sessions prepare students for their thesis, covering research design, data collection, and analysis. Computational labs provide hands-on experience with programming, simulation, and modelling tools. Project work provides hands-on experience with mathematical modelling, computational methods, and data analysis. Seminars provide opportunities for presenting research findings and debating current issues in mathematical modelling. Guest lectures from experienced mathematicians, data scientists, and researchers provide practical insights. The programme culminates in a supervised research thesis on a mathematical modelling topic.
The trade offs
In its favour
- Programme trains advanced data professionals for decision-making across multiple sectors.
- TTU offers competitive fees at approximately KES 155,750/year for science-based masters.
- Programme accepts diverse backgrounds including engineering, economics, and biological sciences.
- Graduates are eligible for SIAM and AMU professional memberships.
Against it
- Only one university (TTU, public) confirmed offering this specific programme.
- No private university confirmed offering this programme.
- Fee data is from an older fee structure and may not reflect current rates.
- Programme requires strong quantitative background, limiting access for non-quantitative graduates.
What it costs
Tuition at both ends of the market, and how to pay for it.
What it costs, and where
Against 243 science coursesAnnual tuition in Kenyan shillings, rounded. The upright tick is the median for this field, so a bar sitting entirely to its right is an expensive programme by the standards of its own subject.
The fine print
TTU unverified. USIU ~295K/yr (usiu.ac.ke). Kabarak ~150K/yr (kabarak.ac.ke).
HELB postgraduate loans are available for Kenyan students. TTU may offer scholarships for eligible students. AMU may offer grants for mathematics research. Some research institutions, government agencies, and industry bodies may sponsor staff for postgraduate study.
Funding options
HELB Postgraduate Loan
TTU Scholarship
AMU Grant
Scholarships
3 recordedHELB Postgraduate Loan
LoanKsh 200,000Kenyan
Kenyan students pursuing postgraduate studies at recognised universities.
TTU Scholarship
ScholarshipKsh 155,750Kenyan
Taita Taveta University offers scholarships for eligible postgraduate students.
AMU Grant
ScholarshipKsh 100,000
AMU may offer grants for mathematics research and education in Africa.
Getting in
The grades, the alternatives, and who accredits the award.
What you need
- KCSE mean grade
- N/A (Postgraduate)
- Alternative entry
- TTU accepts Bachelor's degrees in Mathematics, Statistics, Engineering, Economics, or Biological/Biomedical/Ecological Sciences with strong quantitative background. Lower Second Class may be considered with proven research ability. Contact TTU for specific admission requirements.
How you are assessed
4 componentsCoursework and Continuous Assessment
Coursework30% of the mark
Continuous assessment through coursework assignments, computational projects, seminar presentations, and class participation.
Written Examinations
Examination70% of the mark
Written examinations covering mathematical modelling, computational methods, differential equations, and stochastic modelling.
Computational Project Assessment
Project40% of the mark
Practical assessment through computational projects, modelling exercises, simulations, and demonstrating mathematical modelling skills.
Research Thesis
Research100% of the mark
Original supervised research thesis on a mathematical modelling topic, demonstrating mastery of research methods and mathematical modelling knowledge, assessed through written submission and oral defence.
Accreditation
The programme is accredited by the Commission for University Education (CUE). Taita Taveta University (public) offers MSc in Mathematical Modelling through the School of Science and Informatics. The programme meets CUE standards for postgraduate training in mathematical modelling. Graduates are eligible for SIAM and AMU professional memberships.
Accredited by
Commission for University Education (CUE)
Academic accreditationRequired
Programme accredited by CUE. Taita Taveta University (public) offers MSc in Mathematical Modelling through the School of Science and Informatics. The programme meets CUE standards for postgraduate training in mathematical modelling. Graduates are eligible for SIAM and AMU professional memberships.
Where it leads
The roles it opens, and what you leave with.
Where graduates go
6 rolesData Scientist
High demandKsh 120,000 to Ksh 500,000
Applies data science methods, overseeing analytics, modelling, ML, and managing data science.
Quantitative Analyst
High demandKsh 120,000 to Ksh 500,000
Develops quantitative models, overseeing modelling, analysis, analytics, and managing quantitative analysis.
Operations Research Analyst
Moderate demandKsh 100,000 to Ksh 450,000
Conducts operations research, overseeing optimisation, modelling, analysis, and managing operations research.
Mathematical Modeller
Moderate demandKsh 100,000 to Ksh 450,000
Develops mathematical models, overseeing formulation, analysis, simulation, and managing mathematical models.
Research Scientist
Moderate demandKsh 100,000 to Ksh 450,000
Conducts mathematical research, overseeing research, modelling, analysis, and managing research.
Mathematics Lecturer
Moderate demandKsh 100,000 to Ksh 450,000
Teaches mathematics at university or college level, overseeing instruction, research, and academic supervision.
Graduate outcomes
Graduates pursue careers as data scientists, quantitative analysts, operations research analysts, mathematical modellers, research scientists, and lecturers in mathematics across research institutions, government agencies, financial institutions, technology firms, and universities.
Where these fields lead
8 careers- Career Guidance & Labour Market Information CounselorEducation11Low exposure
- School Guidance CounselorEducation17Low exposure
- CrystallographerScience19Low exposure
- StatisticsScience20Low exposure
- Motor Vehicle MechanicEducation21Low exposure
- MycologistScience21Low exposure
- OceanographerScience21Low exposure
- Computational BiologistScience22Low exposure
Tools you will learn
MATLAB
SoftwarePrimary
MATLAB for mathematical computing and modelling, covering modelling, simulation, analysis, and managing computational mathematics.
Python
Software
Python for data analysis and scientific computing, covering data, modelling, analysis, and managing computational mathematics.
R
Software
R for statistical analysis and modelling, covering data, statistics, analysis, and managing statistical models.
Mathematica
Software
Mathematica for symbolic and numerical computation, covering computation, modelling, analysis, and managing mathematical computing.
Industry links
Common misconceptions
Mathematical modelling is just about solving equations.
Mathematical modelling covers comprehensive formulation, analysis, simulation, validation, and computational methods beyond just solving equations.
This programme is only for pure mathematicians.
Mathematical modelling skills are valuable for engineers, economists, biologists, and data scientists beyond just pure mathematicians.
Computational mathematics is just about programming.
Computational mathematics covers comprehensive algorithms, numerical methods, simulation, and analysis beyond just programming.
Stochastic modelling is just about probability.
Stochastic modelling covers comprehensive processes, randomness, simulation, and applications beyond just probability.
Mathematical modelling careers are limited in Kenya.
Kenya's growing data economy, financial sector, and research institutions create demand for mathematical modelling professionals.
Optimisation is just about finding the best solution.
Optimisation covers comprehensive techniques, constraints, linear, nonlinear, and integer programming beyond just finding the best solution.
Related courses
Further reading
Fees and entry marks for Master of Science in Mathematical Modelling are restated every intake. Save it and the app keeps this version, so you can see what changed when it does.