About this course
Develop the analytic and professional skills for success in the data science on this Data & Decision Analytics MSc. You’ll learn advanced level mathematical modelling, statistical analysis, and computation.
This UK master’s course will give you the skills and knowledge to make better decisions based on data. There is also a strong focus on real work experience, with opportunities for summer projects in a range of industries.
Through this degree you’ll learn:
- programming skills in R and in Python
- advanced theory and methods of applied statistics
- practical application of operational research
- modelling of deterministic and stochastic systems
- industry career skills working on a project with an external organisation
You'll take on 3-month summer project which can be in operational research, statistics, data science or a combination of each. This is excellent preparation if you want to go onto a PhD in one of these areas.
There are 2 options for this project:
- The opportunity to compete for a 3-month project with an external organisation
- An internal project linked to the latest research led by one of our academics
You'll also get the chance to meet with the CORMSIS Business Advisory Board which is represented by major companies including; Tesco, Shell, British Airways and HM Revenue & Customs. They ensure this MSc continues to be fresh and relevant to the needs of employers, so you’ll have excellent employment prospects.
We regularly review our courses to ensure and improve quality. This course may be revised as a result of this. Any revision will be balanced against the requirement that the student should receive the educational service expected. Find out why, when, and how we might make changes.
Our courses are regulated in England by the Office for Students (OfS).
Course lead
The leader for this course is Dr Hou-Duo Qi, who’s current research interest is on matrix optimisation with applications in finance and statistics. Examples include the (low-rank) nearest correlation matrix problem from finance and convex quadratic semidefinite programming in multidimensional scaling. Find out more on Dr Hou-Duo Qi’s staff profile page.
Learn more about this subject area
Course location
This course is based at Highfield.
Awarding body
This qualification is awarded by the University of Southampton.
Download the Course Description Document
The Course Description Document details your course overview, your course structure and how your course is taught and assessed.
Entry requirements
You’ll need a 2:1 degree in a subject that involves some quantitative training, such as:
- computer science
- economics
- engineering
- mathematics
- physics
- statistics
Find the equivalent international qualifications for your country.
English language requirements
If English isn't your first language, you'll need to complete an International English Language Testing System (IELTS) to demonstrate your competence in English. You'll need all of the following scores as a minimum:
IELTS score requirements
- overall score
- 6.5
- reading
- 6.0
- writing
- 6.0
- speaking
- 6.0
- listening
- 6.0
We accept other English language tests. Find out which English language tests we accept.
Pre-masters
If you don’t meet the English language requirements, you can achieve the level you need by completing a pre-sessional English programme before you start your course.
If you don’t meet the academic requirements, you can complete a pre-master's programme through our partnership with ONCAMPUS. Learn more about the programmes available.
Got a question?
Please contact us if you're not sure you have the right experience or qualifications to get onto this course.
Email: enquiries@southampton.ac.uk
Tel: +44(0)23 8059 5000
Course structure
This is a full-time MSc which runs over 12-months from September to the following September. There are 2 semesters of taught material. You’ll then complete an MSc project (usually in the summer).
In semesters 1 and 2 you'll study a combination of modules that everyone on the course must study, and additional modules you'll get to choose from a range of options. These will provide you with the necessary foundations in operational research and statistics.
Want more detail? See all the modules in the course.
Modules
The modules outlined provide examples of what you can expect to learn on this degree course based on recent academic teaching. As a research-led University, we undertake a continuous review of our course to ensure quality enhancement and to manage our resources. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand. Find out why, when and how we might make changes.
Year 1 modules
You must study the following modules :
Computational Machine Learning and Optimisation
This module will introduce you to some of the main approaches used for data analysis and machine learning. Students will gain knowledge and understanding of different computational machine learning methods, and gain skills in applying them to analyse dat...
Data Mining and Analytics
The module provides an introduction to data analytics and data mining. It will combine practical work using R and SQL with an introduction to some of the theory behind standard data mining techniques.
Deterministic OR Methods for Data Scientists
This module aims to introduce the student to some of the main deterministic techniques that are used in operational research, namely linear and integer programming. The process of modelling problems of a practical nature as a linear or integer program wil...
Introduction to Python
This module aims to teach students the fundamentals of writing structured computer programs, applicable using any high level programming language. However, students will be shown the special features of Python that makes this language especially useful fo...
Likelihood and Bayesian Inference
This module develops methods for conducting inference about parametric statistical models. The techniques studied are general and applicable to a wide range of statistical models, including simple models for identically distributed responses and regressio...
Statistical Computing for Data Scientists
This module will provide an introduction to basic statistical programming in R. It consists of lecturers and associated practical sessions for students to gain hands-on experience of statistical programming.
Stochastic OR Methods for Data Scientists
Stochastic OR Methods provides the students with a grounding in the stochastic elements of operational research. Models and examples are given to demonstrate applications of the topics. Discrete event simulation is taught via lectures and computer worksho...
You must also choose from the following modules :
Analytical Consultancy Skills
The first case study is run by a company over one day and focuses on the modelling of a problem that is of current interest. The second case study runs over four days and requires a complex problem to be solved. The techniques used to tackle the problems ...
Computer-based statistical modelling
The aim of the course is to provide a modern view of computer-based data analysis, from the statistical point of view. The course is intended for students with a solid basic background in probability, statistical methods, and computing, and who aim to bu...
Design of Experiments
When planning experiments, it is essential that the data collected are as relevant and informative as possible. The statistical principles for the design of experiments include the choice of optimal or good treatments sets and appropriate replication of t...
Financial Portfolio Theory
The module aims to introduce the students to the basics of portfolio theory. Beginning with a summary of the reasons why both private investors and large institutional investors might wish to own share portfolios, the module progresses to consider how ris...
Flexible Regression
This module will introduce and develop flexible statistical modelling methods that allow for general and complex forms of data to be modelled, extending ideas already encountered in earlier modules on linear and/or generalised linear modelling. The two ma...
Forecasting
The module will introduce students to time series models and associated forecasting methods.
Machine Learning
The purpose of the module will be to introduce students to the fundamentals of machine learning, i.e. computational methods for statistical learning, prediction and decision-making using data. The basic principles of predictive modelling will be outlined,...
Operational Research and Data Science Case Study 1
This module, alongside a second module Operational Research and Data Science Case Study 2, will form an option in Part II of MSc Operational Research, MSc Operational Research with Finance, and MSc Data and Decision Analytics. Both modules will have 30 CA...
Operational Research and Data Science Case Study 2
This module, alongside a second module Operational Research and Data Science Case Study 1, will form an option in Part II of MSc Operational Research, MSc Operational Research with Finance, and MSc Data and Decision Analytics. Both modules will have 30 CA...
Project
Students are allocated a project with an external organisation or on a topic devised by a member of staff in the Operational Research or Management Sciences group at the University of Southampton.
Project Management
The global and rapid growth of managing by projects in every sector, industry, and company type has led to the development of pan-sector theories and bodies of knowledge in project management. The specific nature of projects as temporary and unique activi...
Project Risk Management
Project risk management has evolved significantly over many years, but there are conflicting views about what constitutes best practice. This course provides an overview of best practice as outlined in the course text with a critical comparison of alterna...
Revenue Management
The module provides an introduction to the theory and practice of Revenue Management
Learning and assessment
Learning
The learning activities for this course include:
- careers talks from external organisations
- employability skills training
- computer programming
- collecting and analysing data
- using IT for optimisation, simulation, and statistical software
- coursework
- individual and group projects
Assessment
We’ll assess you through:
- coursework and essays
- a dissertation
- group essays
- individual and group projects
- written exams
Dissertation
You'll need to submit a dissertation on your project work soon after the end of the taught period of study. You'll be required to complete their work by the middle of September.
Academic Support
Your contact hours will vary depending on your module/option choices. Full information about contact hours is provided in individual module profiles.
Careers
Data science has seen an unparalleled expansion as the data-driven economy grows. Having a good understanding of the process of deriving actionable insights from data opens-up a huge amount of career options.
Increasingly organisations require skilled professionals who can handle large datasets and managers who can utilise the resulting analysis to make impactful decisions. The nature of the work brings MSc Data and Decision Analytics graduates into early contact with senior management which can offer opportunities for rapid career advancement.
Careers services at Southampton
We're a top 20 UK university for employability (QS Graduate Employability Rankings 2022). Our Careers, Employability and Student Enterprise team will support you throughout your time as a student and for up to 5 years after graduation. This support includes:
- work experience schemes
- CV/resume and interview skills workshops
- networking events
- careers fairs attended by top employers
- a wealth of volunteering opportunities
- study abroad and summer school opportunities
We have a thriving entrepreneurship culture. You'll be able to take advantage of:
- our dedicated start-up incubator, Futureworlds
- a wide variety of enterprise events run throughout the year
- our partnership in the world’s number 1 business incubator, SETsquared
Fees, costs and funding
Tuition fees
Fees for a year's study:
- UK students pay £9,250.
- EU and international students pay £24,200.
Deposit
If you're an international student on a full-time course, we'll ask you to pay £2,000 of your tuition fees in advance, as a deposit.
Your offer letter will tell you when this should be paid and provide full terms and conditions.
Find out about exemptions, refunds and how to pay your deposit on our tuition fees for overseas students page.
What your fees pay for
Your tuition fee covers the full cost of tuition and any exams.
Find out how to pay your tuition fees.
Accommodation and living costs, such as travel and food, are not included in your tuition fees. Explore:
10% alumni discount
If you’re a graduate of the University of Southampton, you could be eligible for a 10% discount on your postgraduate tuition fees.
Postgraduate Master’s Loans (UK nationals only)
This can help with course fees and living costs while you study a postgraduate master's course. Find out if you're eligible.
This course is part of the Shared Scholarship Scheme, an initiative between the UK Department for International Development (DFID) and UK universities to support students from developing commonwealth countries.
You may be eligible for this scholarship if you are:
- from a developing commonwealth country
- would not be able to study a master’s degree in the UK
Southampton Mathematics Postgraduate International Scholarship
A scholarship of £3,000 is available to international students studying for a postgraduate master’s in Mathematics.
Find out more about the Southampton Mathematics Postgraduate International Scholarship, including eligibility and conditions.
Other postgraduate funding options
A variety of additional funding options may be available to help you pay for your master’s study. Both from the University and other organisations.
Funding for EU and international students
Find out about funding you could get as an international student.
How to apply
- Use the 'apply for this course' button on this page to take you to our online application form.
- Search for the course you want to apply for.
- Complete the application form and upload any supporting documents.
- Submit your application.
For further details, read our step by step guide to postgraduate taught applications.
Application deadlines
UK students
The deadline to apply for this course is Wednesday 3 July 2024 - midday UK time.
We advise applying early as applications may close before the expected deadline if places are filled.
International students
The deadline to apply for this course is Wednesday 3 July 2024 - midday UK time.
We advise applying early as applications may close before the expected deadline if places are filled.
Application assessment fee
We’ll ask you to pay a £50 application assessment fee if you’re applying for a postgraduate taught course.
This is an extra one-off charge which is separate to your tuition fees and is payable per application. It covers the work and time it takes us to assess your application. You’ll be prompted to pay when you submit your application which won’t progress until you've paid.
If you're a current or former University of Southampton student, or if you’re applying for certain scholarships, you will not need to pay the fee. PGCE applications through GOV.UK and Master of Research (MRes) degree applications are also exempt. Find out if you’re exempt on our terms and conditions page.
Supporting information
When you apply you’ll need to submit a personal statement explaining why you want to take the course.
You’ll need to include information about:
- your knowledge of the subject area
- why you want to study a postgraduate qualification in this course
- how you intend to use your qualification
References are not required for this programme.
Please include the required paperwork showing your first degree and your IELTS English language test score (if you are a non-native English speaker) with your application. Without these, your application may be delayed.
What happens after you apply
You'll be able to track your application through our online Applicant Record System.
We will aim to send you a decision 6 weeks after you have submitted your application.
If we offer you a place, you will need to accept the offer within 30 working days. If you do not meet this deadline, we will offer your place to another applicant.
Unfortunately, due to number of applications we receive, we may not be able to give you specific feedback on your application if you are unsuccessful.
Equality and diversity
We treat and select everyone in line with our Equality and Diversity Statement.
Got a question?
Please contact us if you're not sure you have the right experience or qualifications to get onto this course.
Email: enquiries@southampton.ac.uk
Tel: +44(0)23 8059 5000
