How to apply

Overview

The details

Course: Optimisation and Data Analytics

Start date: October 2025

Study mode: Full-time

Duration: 1 year

Location: Colchester Campus

Based in: Mathematics, Statistics and Actuarial Science (School of)

Our MSc Optimisation and Data Analytics will appeal if your first degree included mathematics as its major subject. We expect you to have prior knowledge of statistics – for example significance testing or basic statistical distributions – and operational research such as linear programming.

Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Working in this field, you might be identifying future needs for a business, evaluating the time-life value of a customer, or carrying out computer simulations for airlines.

You specialise in areas including:

Continuous and discrete optimisation
Time series econometrics
Heuristic computation
Experimental design
Machine learning
Linear models

Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines.

Our School of Mathematics, Statistics and Actuarial Science has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.

We are genuinely innovative and student-focused. Our research groups are working on a broad range of collaborative areas tackling real-world issues. Here are a few examples:

Our data scientists carefully consider how not to lie, and how not to get lied to with data. Interpreting data correctly is especially important because much of our data science research is applied directly or indirectly to social policies, including health, care and education.
We do practical research with financial data (for example, assessing the risk of collapse of the UK's banking system) as well as theoretical research in financial instruments such as insurance policies or asset portfolios.
We also research how physical processes develop in time and space. Applications of this range from modelling epilepsy to modelling electronic cables.
Our optimisation experts work out how to do the same job with less resource, or how to do more with the same resource.
Our pure maths group are currently working on two new funded projects entitled ‘Machine learning for recognising tangled 3D objects' and ‘Searching for gems in the landscape of cyclically presented groups'.
We also do research into mathematical education and use exciting technologies such as electroencephalography or eye tracking to measure exactly what a learner is feeling. Our research aims to encourage the implementation of ‘the four Cs' of modern education, which are critical thinking, communication, collaboration, and creativity.

Why we're great.

This course will appeal to you if your first degree included mathematics as the major subject, and you have prior knowledge of statistics.
You specialise in areas including continuous and discrete optimisation, time series econometrics, and experimental design.
We have an international reputation for our work on optimisation, probability and applied statistics.

Our expert staff

Our School is committed to providing you with the academic support you need to succeed. Our flexible policy means some staff are always available, whilst others maintain regular drop-in times. Staff are always happy to arrange appointments for longer discussions, and no issue is too big or too small.

Our staff have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals like Communications in Algebra, Studia Logica, International Journal of Algebra and Computation, SIAM Journal in Optimization, IEEE Evolutionary Computation, Computers and Operations Research, Ecology, Journal of Mathematical Biology, and Journal of Statistical Applications in Genetics and Molecular Biology.

Specialist facilities

Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
We have our own computer labs for the exclusive use of students in the School of Mathematics, Statistics and Actuarial Science – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
We host events and seminars throughout the year
Our students run a lively Mathematics Society, an active and social group where you can explore your interest in your subject with other students

Your future

Our MSc Optimisation and Data Analytics will equip you with employability skills like problem solving, analytical reasoning, data analysis, and mathematical modelling, as well as training you in independent work, presentation and writing skills.

Your exposure to current active research areas, such as decomposition algorithms, prepares you for further study at doctoral level. Graduates of this course now hold key positions in government, business and academia, and work for global companies such as Ocado Technology and Dunnhumby, as well as for HM Revenue & Customs, as data and business intelligence analysts.

We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology, and our staff are strongly committed to research and to the promotion of graduate activities.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Entry requirements

UK entry requirements

A 2:2 degree or international equivalent in one of the following subjects:

Applied Mathematics
Biostatistics
Computer Science
Economic Statistics
Economics
Mathematics
Operational Research
Pure Mathematics
Statistics

Any other 2:2 degree in any subject which includes three modules from the below lists:

One module, from:

Advanced Maths (I/II/III)
Calculus (I/II/III) - AKA Mathematical Analysis
Engineering Maths (I/II/III)
Maths (I/II/III)

And

One module, from:

Advanced Maths (I/II/III)
Engineering Maths (I/II/III)
Maths (I/II/III)
Statistics or Probability

And

One additional relevant module, from:

Advanced Maths (I/II/III)
Algebra
Analysis
Complex Numbers
Differential Equations
Engineering Maths (I/II/III)
Maths (I/II/III)
Numerical Methods
Optimisation (Linear Programming)
Programming Language (R or MATLAB or Python)
Regression
Another module in Probability or Statistics
Stochastic Process

Applicants with a degree below 2:2 or equivalent will be considered dependent on any relevant professional or voluntary experience and previous modules studied.

International & EU entry requirements

We accept a wide range of qualifications from applicants studying in the EU and other countries. Get in touch with any questions you may have about the qualifications we accept. Remember to tell us about the qualifications you have already completed or are currently taking.

Sorry, the entry requirements for the country that you have selected are not available here. Please contact our Graduate Admissions team at pgquery@essex.ac.uk to request the entry requirements for this country.

English language requirements

If English is not your first language, we require IELTS 6.0 overall with a minimum component score of 5.5 in all components.

If you do not meet our IELTS requirements then you may be able to complete a pre-sessional English pathway that enables you to start your course without retaking IELTS.

Additional Notes

The University uses academic selection criteria to determine an applicant’s ability to successfully complete a course at the University of Essex. Where appropriate, we may ask for specific information relating to previous modules studied or work experience.

Structure

Course structure

Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field. The following modules are based on the current course structure and may change in response to new curriculum developments and innovation.

We understand that deciding where and what to study is a very important decision for you. We'll make all reasonable efforts to provide you with the courses, services and facilities as described on our website and in line with your contract with us. However, if we need to make material changes, for example due to significant disruption, we'll let our applicants and students know as soon as possible.

Components and modules explained

Components

Components are the blocks of study that make up your course. A component may have a set module which you must study, or a number of modules from which you can choose.

Each component has a status and carries a certain number of credits towards your qualification.

Status	What this means
Core	You must take the set module for this component and you must pass. No failure can be permitted.
Core with Options	You can choose which module to study from the available options for this component but you must pass. No failure can be permitted.
Compulsory	You must take the set module for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Compulsory with Options	You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Optional	You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.

The modules that are available for you to choose for each component will depend on several factors, including which modules you have chosen for other components, which modules you have completed in previous years of your course, and which term the module is taught in.

Modules

Modules are the individual units of study for your course. Each module has its own set of learning outcomes and assessment criteria and also carries a certain number of credits.

In most cases you will study one module per component, but in some cases you may need to study more than one module. For example, a 30-credit component may comprise of either one 30-credit module, or two 15-credit modules, depending on the options available.

Modules may be taught at different times of the year and by a different department or school to the one your course is primarily based in. You can find this information from the module code. For example, the module code HR100-4-FY means:

100

The department or school the module will be taught by.

In this example, the module would be taught by the Department of History.

The module number.

The UK academic level of the module.

A standard undergraduate course will comprise of level 4, 5 and 6 modules - increasing as you progress through the course.

A standard postgraduate taught course will comprise of level 7 modules.

A postgraduate research degree is a level 8 qualification.

The term the module will be taught in.

AU: Autumn term
SP: Spring term
SU: Summer term
FY: Full year
AP: Autumn and Spring terms
PS: Spring and Summer terms
AS: Autumn and Summer terms

COMPONENT 01: CORE WITH OPTIONS

(60 CREDITS)

COMPONENT 02: COMPULSORY

Nonlinear Programming

(15 CREDITS)

How do you apply an algorithm or numerical method to a problem? What are the advantages? And the limitations? Understand the theory and application of nonlinear programming. Learn the principles of good modelling and know how to design algorithms and numerical methods. Critically assess issues regarding computational algorithms.

View Nonlinear Programming on our Module Directory

COMPONENT 03: COMPULSORY

Combinatorial Optimisation

(15 CREDITS)

In this module you will learn techniques underpinning algorithms for studying integer-valued systems, and apply these algorithms to solve integer and mixed integer problems with cutting-plane algorithms.

View Combinatorial Optimisation on our Module Directory

COMPONENT 04: COMPULSORY

Introduction to Programming in Python

(15 CREDITS)

The aim of this module is to provide an introduction to computer programming for students with little or no previous experience. The Python language is used in the Linux environment, and students are given a comprehensive introduction to both during the module. The emphasis is on developing the practical skills necessary to write effective programs, with examples taken principally from the realm of data processing and analysis. You will learn how to manipulate and analyse data, graph them and fit models to them. Teaching takes place in workshop-style sessions in a software laboratory, so you can try things out as soon as you learn about them.

View Introduction to Programming in Python on our Module Directory

COMPONENT 05: COMPULSORY

Dynamic programming and reinforcement learning

(15 CREDITS)

Are you interested in understanding how AlphaGo was able to beat a top Go player? In this module, you will learn about the models behind successful stories of Reinforcement Learning, where a machine (agent) makes sequential decisions to reach an optimal goal. The lectures will be complemented with Lab sessions where we will take advantage of the Open AI Gym environments, allowing us to train our agents to perform tasks such as playing videogames (Atari) and more.

View Dynamic programming and reinforcement learning on our Module Directory

COMPONENT 06: COMPULSORY

Data Visualisation

(15 CREDITS)

In a world increasingly driven by data, the need for analysis and visualisation is more important than ever. In this module you will look at data through the eyes of a numerical detective. You will work on the lost art of exploratory data analysis, reviewing appropriate methods for data summaries with the aim to summarise, understand, extract hidden patterns and identify relationships. You will then work on graphical data analysis, using simple graphs to understand the data, but also advanced complex methods to scrutinise data and interactive plots to communicate data information to a wider audience. For data analysis and visualisations you will use R-studio, and a combination of R-shiny applications and google visualisations for interactive plotting.

View Data Visualisation on our Module Directory

COMPONENT 07: COMPULSORY WITH OPTIONS

(45 CREDITS)

COMPONENT 08: COMPULSORY

Research Skills and Employability

(0 CREDITS)

What skills do you need to succeed during your studies? What about after university? How will you harness your knowledge and soft skills to realise your career goals? This module helps you take an active role in developing transferrable skills and capitalising on your unique background. As well as broad reflection on your professional development, this module will help you explore different career directions and prepare you for the application process, supported by an advisor from within the department.

View Research Skills and Employability on our Module Directory

Teaching

Postgraduate Taught students in the School of Mathematics, Statistics and Actuarial Science typically attend two hours of lectures and one class/lab every week, but this will vary dependent upon the module
Core components can be combined with optional modules, to enable you to gain either in-depth specialisation or a breadth of understanding
Learn to use LATEX to produce a document as close as possible to what professional mathematicians produce in terms of organisation, layout and type-setting
Our postgraduates are encouraged to attend conferences and seminars

Assessment

Courses are assessed on the results of your written examinations, together with continual assessments of your practical work and coursework

Dissertation

You will be provided with a list of dissertation titles or topics proposed by staff and it may be possible to propose a project of your own
Most dissertations are between 10,000 and 30,000 words in length. However, these are guidelines, not mandatory word counts
Close supervision by academic staff

Fees and funding

Home/UK fee

£10,500

International fee

£22,750

Masters fees and funding information

Research (e.g. PhD) fees and funding information

What's next

We hold Open Days for all our applicants throughout the year. Our Colchester Campus events are a great way to find out more about studying at Essex, and give you the chance to:

tour our campus and accommodation
find out answers to your questions about our courses, student finance, graduate employability, student support and more
meet our students and staff

If the dates of our organised events aren’t suitable for you, feel free to get in touch by emailing tours@essex.ac.uk and we’ll arrange an individual campus tour for you.

2025 Open Days (Colchester Campus)

Saturday 21 June 2025 - June Open Day

Saturday 20 September 2025 - September Open Day

Saturday 8 November 2025 - November Open Day

Find out more

You can apply for this postgraduate course online. Before you apply, please check our information about necessary documents that we'll ask you to provide as part of your application.

We aim to respond to applications within two weeks. If we are able to offer you a place, you will be contacted via email.

For information on our deadline to apply for this course, please see our ‘how to apply' information.

Applicants with an undergraduate degree from our School of Mathematics, Statistics and Actuarial Science, or who are working towards one, should first contact our admissions staff: maths@essex.ac.uk.

A sunny day with banners flying on Colchester Campus Square 4.

Set within 200 acres of award-winning parkland - Wivenhoe Park and located two miles from the historic city centre of Colchester – England's oldest recorded development. Our Colchester Campus is also easily reached from London and Stansted Airport in under one hour.

Find out more

View from Square 2 outside the Rab Butler Building looking towards Square 3

If you live too far away to come to Essex (or have a busy lifestyle), no problem. Our 360 degree virtual tour allows you to explore the Colchester Campus from the comfort of your home. Check out our accommodation options, facilities and social spaces.

At Essex we pride ourselves on being a welcoming and inclusive student community. We offer a wide range of support to individuals and groups of student members who may have specific requirements, interests or responsibilities.

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