School of Computing, Electronics and Mathematics

BSc (Hons) Data Modelling and Analytics

Gain expertise in a wide range of topics, including Big Data analysis, modern visualization techniques and social media sentiment analysis, and develop the kind of expert data modelling knowledge and analytics skills that are highly sought after by industry. This course is underpinned by and enhanced with a focus on employability and careers related skills, helping you to develop an extensive transferable skill set alongside comprehensive subject specific knowledge.

You will benefit from research-led teaching and the expertise of leading statisticians, data scientists and mathematicians. You will immerse yourself in industry-relevant practical applications and apply your knowledge to a variety of sectors, from banking and finance to e-commerce, consultancy and government. You’ll distinguish yourself professionally with a degree accredited by the Royal Statistical Society.

Final year entry only

We are not currently recruiting to Year 1 or 2 of this course. Final year entry only.

The Plymouth Mathematics Scholarship

Up to £1,000

Students are automatically paid £500 for an A in Mathematics A level and/or a further sum of £500 for an A in Further Mathematics. This is awarded to home/EU applicants who put us as their firm choice before the 1st August 2019. The scholarship is paid during the first semester of the first year.

There are additional prizes and awards to reward high achievement in later years of the degree.

Mathematical sciences degrees

This is one of the suite of mathematics undergraduate degrees that we offer. You can find out more about the various options at the link below.

Which mathematics degree is right for me?

It’s not too late to apply for September 2019

If you haven’t applied to the University of Plymouth for September 2019 entry, prior to the UCAS deadline, there may still be vacancies on your chosen course.

It’s not too late to apply

Key features

  • Develop expert data modelling knowledge and analytics skills, helping you to stand out to prospective employers.
  • Immerse yourself in industry-relevant practical applications and apply your knowledge to a variety of sectors, from banking and finance to e-commerce, consultancy and government.
  • Collaborate with our research-active analytics experts on a project you are passionate about.
  • Gain expertise in a wide range of topics, including Big Data analysis, modern visualization techniques and social media sentiment analysis.
  • Benefit from research-led teaching and the expertise of leading statisticians, data scientists and mathematicians.
  • We’re very proud of being top in the Guardian Mathematics University League Table for 2019 for satisfaction with the course. We are also fourth for satisfaction with mathematics teaching. This is part of a record of students regularly saying that they enjoy our degrees and teaching.
  • In the UK 2014 Research Excellence Framework 68 per cent of our research papers were classified as World Leading or Internationally Excellent.
  • Gain industrial experience with an optional work placement year.
  • Distinguish yourself professionally with a degree accredited by the Royal Statistical Society*.

Course details

  • Year 1
  • Only final year entry available

    Core modules
    • BPIE113 Stage 1 Mathematics Placement Preparation

      The route to graduate-level employment is found easier with experience. These sessions are designed to assist students in their search for a year-long placement and in their preparation for the placement itself. Such placements are optional but strongly recommended.

    • MATH1601 Mathematical Reasoning

      This module introduces the basic reasoning skills needed to develop and apply mathematical ideas. Clear logical thinking is central to the understanding of mathematics. The module explores fundamental properties of prime numbers, their random generation and use in modern cryptography.

    • MATH1602 Calculus and Analysis

      This module covers key topics in calculus and analysis and prepares students for the rest of their degree. It has an emphasis on proof and rigour and introduces some multi-dimensional calculus together with the reasoning skills needed for the development of modern mathematics. Analysis is the rigorous underpinning of calculus and these key ideas are developed and applied to limits of sequences, series and functions.

    • MATH1603 Linear Algebra and Complex Numbers

      This module explores the concepts and applications of vectors, matrices and complex numbers. The deep connection between algebra and geometry is explored. The techniques that are presented in this module are at the foundation of many areas of mathematics, statistics, physics, and several other applications.

    • MATH1605 Probability with Applications

      An understanding of uncertainty and random phenomena is becoming increasingly important nowadays in daily life and for a variety of fields. The aim of this module in probability is to develop the concept of chance in a mathematical framework. Random variables are also introduced, with examples involving most of the common distributions and the concepts of expectation and variance of a random variable.

    • MATH1610 Numerical and Computational Methods

      This module provides an introduction to appropriate mathematical software, computational mathematics and creating simple computer programs. Students will use mathematical software interactively and also write programs in an appropriate computer language. The elementary numerical methods which underlie industrial and scientific applications will be studied.

    • MATH1611 Geometry and Group Theory

      This module will introduce the foundations of group theory, elementary geometric topology, and Euclidean geometry.

  • Year 2
  • Only final year entry available

    Core modules
    • BPIE213 Stage 2 Mathematics Placement Preparation

      These sessions are designed to help students obtain a year-long placement in the third year of their programme. Students are assisted both in their search for a placement and in their preparation for the placement itself.

    • MATH258 Quantitative Financial Modelling

      This module provides an introduction to statistical and mathematical techniques applied to financial data.

    • MATH2601 Advanced Calculus

      In this module the geometrical and dynamical concepts needed to describe higher-dimensional objects are introduced. This includes vector calculus techniques and new forms of integration such as line integration. Students also explore the relations between integration and differentiation in higher dimensional hyperspaces. This knowledge is applied to various real world problems.

    • MATH2602 Statistical Inference and Regression

      The module provides a mathematical treatment of statistical inference, including confidence intervals and hypothesis testing. Methods of estimation are explored, focusing on maximum likelihood estimation. The module also demonstrates the underlying mathematical theory of the general linear model, through a variety of applications, using professional software.

    • MATH2603 Ordinary Differential Equations

      The module aims to provide an introduction to different types of ordinary differential equations and the analytical and numerical methods needed to obtain their solutions. Extensive use is made of computational mathematics packages. Applications to mechanical and chemical systems are considered as well as the chaotic behaviour seen in climate models.

    • MATH2604 Mathematical Methods and Applications

      Vector calculus is extended to higher dimensions and applied to a range of important scientific problems primarily from classical mechanics and cosmology. Differential and integral calculus is applied to the solution of differential equations and the orthogonal functions bases are constructed. The crucial mathematical concepts of integral transforms (Fourier and Laplace) and Fourier series are introduced.

    • MATH2605 Operational Research and Monte Carlo Methods

      This module gives students the opportunity to work on open-ended case studies in operational research (OR) and Monte Carlo methods, both of which are important methods in, for example, industry and finance. It allows students to work on their own and in teams to develop specific skills in OR and programming as well as refining their presentation and communication skills. The skills in computational simulation developed in this module have many applications.

  • Optional placement year
  • Only final year entry available

    Core modules
    • BPIE331 Mathematics and Statistics Placement

      A 48-week period of professional training is spent as the third year of a sandwich programme while undertaking an approved placement with a suitable company. This provides an opportunity for the student to gain experience of how mathematics is used in a working environment, to consolidate their previous study and to prepare for the final year and employment after graduation. Recent placement providers include GSK, the Office for National Statistics, NATS (air traffic control) and VW Group.

  • Final year
  • You will study data modelling topics equipping you with the analytical skills needed by business and industry, together with predictive analytics for forecasting financial data and optimisation for efficient decision making. You may undertake a series of mini-projects on analytics topics or work with an analytics expert on a project of your choice about Big Data or social media sentiment analysis.

    Core modules
    • MATH3609 Optimisation, Networks and Graphs

      This module introduces the mathematics of continuous and discrete optimisation. It provides the theoretical background and practical algorithmic techniques required to model and solve a diverse range of problems.

    • MATH3613 Data Modelling

      This module provides an employment relevant tool box of statistical modelling techniques and a rigorous treatment of the underlying mathematics. The Bayesian framework for statistical inference is developed and compared with the classical approach. Important computational algorithms, including Markov Chain Monte Carlo, are described. Application-rich modelling problems are considered.

    • MATH3614 Medical Statistics

      The content includes the design and analysis of clinical trials, including crossover and sequential designs and an introduction to meta-analysis. Epidemiology is studied, including case-control and cohort studies. Survival analysis is covered in detail. Computer packages are used throughout.

    • MATH3623 Financial Statistics

      This module introduces students to the concepts and methods of financial time series analysis and modelling and to a variety of financial applications. The module reviews the necessary univariate and multivariate time series models and inferential techniques. Model selection, forecasting and the ‘curse of dimensionality’ problem for high dimensional modelling are treated both analytically and computationally. The R programming language is widely used in this module.

    Optional modules
    • ACF302 Investment Management

      This module is designed to provide a broad understanding of equities and bonds as investments. It considers their pricing and use in investment management along with that of derivatives. In addition core concepts in finance are covered including market efficiency, diversification, risk, portfolio building and evaluation.

    • MATH3605 Partial Differential Equations

      This module introduces partial differential equations using real-life problems. It provides a variety of analytic and numerical methods for their solution. It includes a wide range of applications including heat diffusion and the Tsunami wave.

    • MATH3622 Analytics in Context

      This module is designed to be an alternative to the individual project. In the module students perform structured investigations on a variety of advanced topics in mathematics and statistics. Students give oral presentations and write up a journal style article on their work. Some of these articles have been published in the University of Plymouth’s Student Scientist journal.

    • MATH3628 Project

      Students who have identified a topic of particular interest have the opportunity to study it in a final year project. Students work individually and independently, with help and advice from a supervisor, on the chosen topic. The project is assessed through presentations and the preparation of a dissertation. This is a major piece of work and the project counts as two modules

Every undergraduate taught course has a detailed programme specification document describing the course aims, the course structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

The following programme specification represents the latest course structure and may be subject to change:

BSc Data Modelling and Analytics programme specification 5763

The modules shown for this course are those currently being studied by our students, or are proposed new modules. Please note that programme structures and individual modules are subject to amendment from time to time as part of the University’s curriculum enrichment programme and in line with changes in the University’s policies and requirements.

Entry requirements

UCAS tariff

120 - 128

A typical offer is 120 points to include minimum of 2 A levels, including grade B in A level mathematics or B in further mathematics or A level mathematics and statistics or mathematics (pure and applied) excluding general studies. Mathematics (mechanics) accepted as mathematics.

International Baccalaureate: 30 overall to include 5 at Higher Level mathematics. English must be included.

18 Unit BTEC National Diploma/QCF Extended Diploma: DDM to include a distinction in a mathematics subject: Individual interview/diagnostic test will be required.

BTEC National Diploma modules
If you hold a BTEC qualification it is vital that you provide our Admissions team with details of the exact modules you have studied as part of the BTEC. Without this information we may be unable to process your application quickly and you could experience significant delays in the progress of your application to study with us. Please explicitly state the full list of modules within your qualification at the time of application.

Pass Access to HE Diploma (i.e. mathematics, science, combined) with at least 33 credits at merit and/or distinction and to include at least 12 credits in mathematics units with merit. Individual interview/diagnostic test please contact admissions@plymouth.ac.uk for further information.

Other qualifications are also welcome and will be considered individually, as will be individuals returning to education, email maths@plymouth.ac.uk

Students may also apply for the BSc (Hons) Mathematics with Foundation Year. Successful completion of the foundation year guarantees automatic progression to the first year of any of our mathematics courses.

Direct entrants into years other than the first year will be considered individually.

For a full list of all acceptable qualifications please refer to our tariff glossary.


Fees, costs and funding

New Student 2018 2019
Home/EU £9,250 £9,250
International £13,000 £13,400
Part time (Home/EU) To be confirmed To be confirmed
Full time fees shown are per annum. Part time fees shown are per a number of credits. Please note that fees are reviewed on an annual basis. Fees and the conditions that apply to them shown in the prospectus are correct at the time of going to print. Fees shown on the web are the most up to date but are still subject to change in exceptional circumstances.

Undergraduate scholarships for international students

To reward outstanding achievement the University of Plymouth offers scholarship schemes to help towards funding your studies.

Find out whether you are eligible and how you can apply

Scholarships and awards

For 2019 entry, we have the following scholarship:
  • Mathematics Scholarship of up to £1,000: students are automatically paid £500 for an A in Mathematics A level and/or £500 for an A in Further Mathematics A level. This is awarded to anybody who puts us as their firm choice before the 1st of August 2019. The scholarship is paid in the first semester of the first year.
  • There are additional prizes and awards to reward high marks in later years.

How to apply

All applications for undergraduate courses are made through UCAS (Universities and Colleges Admissions Service). 

UCAS will ask for the information contained in the box at the top of this course page including the UCAS course code and the institution code. 

To apply for this course and for more information about submitting an application including application deadline dates, please visit the UCAS website.

Support is also available to overseas students applying to the University from our International Office via our how to apply webpage or email international-admissions@plymouth.ac.uk.

What's it all about?

This course has been developed to equip you with the kind of real world knowledge and skills that are relevant to, and sought after by business and industry today. 

Data modelling topics will sharpen your analytical skills, and you will learn about predictive analytics and their application to financial data forecasting. You will study optimisation and have the opportunity to learn data mining techniques for identifying clusters in high-dimensional data.

If you want to develop your analytics skills and knowledge further you can opt to carry out a mini project, or select to study an area of particular interest to you, such as Big Data or social media sentiment analysis, and benefit from the support and input of one of our analyitics experts.


Career progression

Throughout your studies subject specific material will be underpinned by and enhanced with a focus on employability and careers related skills.

As a graduate from this course you’ll benefit from a large choice of highly rewarding job opportunities. In addition your extensive transferable skill set and freshly acquired subject-specific knowledge will ensure that you’re prepared for rapid career advancement.

Career opportunities include: analytics specialists, analytics technology consultants and social media analysts in sectors such as banking and finance, e-commerce, consultancy and government. Graduates in data modelling and analytics are often highly sought after for managerial positions in international companies.

Will I get individual support?

You’ll be well supported by our lecturers who have an open door policy and run a tutorial system, that offers an exceptional level of academic and pastoral advice.

What if I am an international student?

If you’re an international student you can rest assured that you’ll benefit from our unparalleled experience, gained from helping over 200 international students successfully complete our final year course.  

You’ll benefit from a friendly and welcoming atmosphere and a variety of opportunities to mix with native English speakers.  One of our recent graduates from Hong Kong said:

“I lived in a student hall with seven flatmates, all of them British. They were really supportive.”
Hilary Tse Kar Man - graduate.

Some feedback from our students

We’re proud of our students and graduates. Here’s what they had to say about studying data modelling and analytics:

“The lecturers provided great support and advice on career development”
Betty Chan Suk Man - graduate.
“Our coursework and projects use real life data and so provide us with experience of applying the analytical techniques that we study”.
Elegance Lam Ting Pui - graduate.

More generally, in the latest National Student Survey 97 per cent of our graduates were satisfied with the quality of the course.

What about research?

The programme is taught by world leading researchers with an international reputation in research and teaching, offering a broad range of data modelling material and supervising projects in a variety of analytics topics.

This degree equips you with valuable skills in mathematics, data analysis and modelling, giving you excellent career prospects as well as the possibility to progress to a research degree.

Data Modelling and Analytics staff