Postgraduate Diploma in Mathematical Modelling
| Program start date | Application deadline |
| 2024-02-26 | - |
| 2024-07-15 | - |
| 2025-03-03 | - |
| 2025-07-21 | - |
Program Overview
The Postgraduate Diploma in Mathematical Modelling at the University of Auckland equips students with advanced knowledge and skills in interdisciplinary mathematical modelling. The program focuses on practical application, computational methods, and problem-solving abilities, preparing graduates for careers in data science, engineering, finance, and other fields where mathematical modelling is essential. The curriculum combines core courses with a wide range of electives, allowing students to tailor their learning experience to their interests and career aspirations.
Program Outline
Degree Overview
Overview:
The Postgraduate Diploma in Mathematical Modelling (PGDipMathModel) at the University of Auckland is aimed at providing students with advanced knowledge and understanding in the field of interdisciplinary mathematical modelling. The program focuses on developing practical skills in current modelling-specific technical advancements and computational methods.
Objectives:
- Equip graduates with the necessary skills and expertise to address contemporary challenges through real-world application of mathematical modelling in various fields.
- Enhance analytical and problem-solving abilities through exposure to diverse modelling techniques.
- Foster independent learning and research skills in the realm of mathematical modelling.
Program Description:
The PGDipMathModel is a 120-point postgraduate program typically delivered over a one-year full-time period. It caters to individuals seeking to upskill in the field of modelling, particularly scientists and engineers. The program curriculum comprises four core courses offered by the Engineering Science and Mathematics departments. Additionally, students can choose from a broad range of elective courses to tailor their learning experience to specific interests and career aspirations.
Benefits:
- Graduates will be equipped with the critical skills and knowledge required to excel in various professional settings, particularly careers involving modelling, simulations, and data analysis.
- The program provides a valuable opportunity for upskilling and professional development for individuals already working in modelling-related fields.
- The curriculum combines theoretical foundations with practical application, preparing graduates for real-world challenges.
Outline
Program Structure:
The PGDipMathModel is built upon a 120-point structure, comprising:
- Core Courses (60 points):
- ENGSCI 711: Advanced Mathematical Modelling
- MATHS 765: Mathematical Modelling
- MATHS 787: Special Topic: Inverse Problems and Stochastic Differential Equations
- Elective Courses (at least 30 points):
- A diverse range of elective courses are offered from various departments, including:
- BIOMENG 771: Musculoskeletal and Orthopaedic Biomechanics
- ECON 721: Econometrics 1
- ECON 723: Econometrics 2
- ENGSCI 712: Computational Algorithms for Signal Processing
- ENGSCI 746: Advanced Modelling and Simulation in Computational Mechanics
- ENGSCI 760: Algorithms for Optimisation
- ENGSCI 761: Integer and Multi-objective Optimisation
- MATHS 761: Dynamical Systems
- MATHS 762: Nonlinear Partial Differential Equations
- MATHS 764
- MATHS 766
- MATHS 769
- MATHS 770: Advanced Numerical Analysis
- OPSMGT 752: Research Methods – Modelling
- PHYSICS 742: Advanced Statistical Mechanics and Condensed Matter
- PHYSICS 743: Waves and Potentials
- PHYSICS 752: Photonics
- PHYSICS 753: The Dynamic Universe
- PHYSICS 780: Advanced Imaging Technologies
- Up to 30 points can be fulfilled by approved 600 and 700 level courses offered by the university.
Course Schedule:
The program offers flexible options for course scheduling, allowing students to choose between full-time or part-time study. Full-time students typically complete the program in one year, while part-time students may take up to four years to finish.
Modules:
The PGDipMathModel consists of various modules, each focusing on specific areas within mathematical modelling.
Assessment
Assessment Methods:
The PGDipMathModel employs various assessment methods to evaluate student learning outcomes. These methods may include:
- Assignments
- Exams
- Projects
- Presentations
- Case studies
Assessment Criteria:
Assessments are designed to evaluate students' understanding of key concepts, analytical skills, problem-solving abilities, and ability to apply theoretical knowledge to real-world scenarios.
Teaching
Teaching Methods:
The PGDipMathModel utilizes various teaching methods to facilitate student learning and engagement, including:
- Lectures
- Tutorials
- Workshops
- Seminars
- Online learning resources
Faculty:
The program is taught by experienced academic staff from the Engineering Science and Mathematics departments, who possess expertise in various modelling techniques and associated applications.
Unique Approaches:
The PGDipMathModel is designed to provide students with a unique learning experience through its focus on practical application and real-world problem-solving. The program also emphasizes interdisciplinary approaches, encouraging students to consider the broader context and implications of mathematical modelling across various fields.
Careers
Potential Career Paths:
Graduates of the PGDipMathModel can pursue various career paths in diverse industries, including:
- Data Science
- Engineering
- Finance
- Operations Research
- Public Policy
- Research and Development
Opportunities:
The program equips graduates with the skills and knowledge to pursue promising career opportunities in various sectors. The demand for skilled mathematical modellers continues to grow across various industries.
Outcomes:
Graduates of the PGDipMathModel are well-prepared to contribute meaningfully to their chosen fields. The program provides them with the ability to apply mathematical modelling effectively in real-world settings and contribute to solving complex problems.
Other
Mathematical Modelling in the News:
The program highlights the growing public awareness of mathematical modelling and its real-world applications, citing examples such as COVID-19 and climate modelling.
University of Auckland Summary
Overview:
The University of Auckland is New Zealand's leading university, renowned for its academic excellence and commitment to research. It offers a wide range of undergraduate and postgraduate programs across various disciplines.
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The University provides a comprehensive range of services for students, including:
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Entry Requirements:
Domestic students:
- A Bachelors degree in a relevant subject with a Grade Point Average of 3.0 or higher in 75 points above Stage IIA
- A Bachelor (Honours) degree in a relevant subject with a Grade Point Average of 3.0 or higher in 120 points above Stage III
International students:
- An undergraduate degree in a relevant subject at a recognised university (or similar institution) with a GPE of 3.0.
Additional requirements for both domestic and international students:
- 15 points from COMPSCI 130, ENGGEN 131, MATHS 162, and 15 points from ENGSCI 311, 313, 314, MATHS 361, or the equivalent as approved by the Programme Director.
- An introductory programming course in MATLAB, C, Python, or similar coding language, and an advanced undergraduate course on partial differential equations, or the equivalents as approved by the Programme Director.
Relevant subjects include:
analytics, applied mathematics, artificial intelligence, computer science, data science, engineering, operations research, physics, software engineering, structural engineering, electrical engineering, statistics, or technology.
Language Proficiency Requirements:
- IELTS Academic: 6.5 overall with no band below 6.0.
