Become a proficient data scientist with a master’s in Data Science at the University of Southampton.
You’ll study the latest techniques and technologies, including data mining, machine learning, and data visualisation. By the end of your studies, you’ll be able to develop original ideas and solve problems using advanced data science methods. You can apply what you have learned in fields such as data journalism, open government and social media.
Data scientists help organisations handle large amounts of data produced by digital technologies. Southampton is recognised around the world as a leader in many of the topics that form our data science curriculum. We offer one of the only data science master's programmes in the UK that covers every subject needed to become a skilled data scientist in industry, government or academia.
Our module teachers use their latest research to inform their teaching in emerging topics like:
Module options are flexible, so you can pursue your interests and adapt the programme to prepare you for your ideal career. We’ll also give you access to dedicated project labs, computer workstations, and infrastructure for large-scale analysis.
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).
Your course leader, Dr Luis-Daniel Ibáñez specialises in Big Data Management and Crowdsourcing.
This course is based at Highfield.
This qualification is awarded by the University of Southampton.
The Course Description Document details your course overview, your course structure and how your course is taught and assessed.
You’ll need an upper 2:1 degree (with a mark of 65% or above) in computer science or a closely related subject:
You must also have a good 2:1 (65%) score in the following:
Find the equivalent international qualifications for your country.
This programme only accepts applicants who have studied at an X1, X2, X3 or X4 institution.
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:
We accept other English language tests. Find out which English language tests we accept.
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.
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
This is a full-time master’s course. You’ll study for 12 months, from September to the following September.
In the first 9 months (semesters 1 and 2) you'll study the taught part of your course.
This is made up of modules that everyone on the course takes, and modules we’ll ask you to choose from a list of options. You'll take exams at the end of both semesters.
You’ll also begin preparing for your final project during semester 1, and continue this work in semester 2.
For the last 3 months, over the summer, you’ll work independently to research and write your dissertation. You’ll have one-to-one meetings with your supervisor during this time to discuss your progress.
Want more detail? See all the modules in the course.
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.
You must study the following modules :
Welcome to the Data Visualisation module! In this course, you would learn about the terminology, concepts and techniques behind visualising data, and will get to use a range of tools to get experience of creating visual representations of data. You will g...
Welcome to the Foundations of Data Science! 'Data scientist' has been described as the sexiest job of the 21st century, with the demand for highly skilled practitioners rising quickly to leverage the increasing amount of data available for study. As the a...
Machine Learning is about extracting useful information from large and complex datasets. The subject is a rich mixture of concepts from function analysis, statistical modelling and computational techniques. The module will cover the fundamental principles...
Your research project will enable you to explore in depth some aspect of your specialist subject area. You will be allocated a project supervisor with whom you will meet and agree a project brief and plan. These must be submitted to, and agreed by, ...
Machine Learning is about extracting useful information from large and complex datasets. The module will cover the practical basis of how learning algorithms are can be applied. You will gain hands-on experience in laboratory-bases sessions. Exclusions...
The Module will prepare students for the summer Research Project and research based coursework exercises. It will give students a grounding in the research methods and techniques necessary in order for planning and successful execution and completion of t...
You must also choose from the following modules :
This module builds on the first year Data Management module to give students a deeper and broader view of the issues involved in database management systems, some of the most complex software in common use.
This module: - Introduces the students to the key issues of interaction of multiple self-interested parties (a.k.a. agents) and gives a broad survey of topics at the interface of theoretical computer science and game theory dealing with such interactions...
Financial markets form the source of a vast number of challenging computational problems. These are not only intellectually challenging from the point of view of computational modelling, but the financial sector is also an employer of a significant fracti...
The challenge of data mining is to transform raw data into useful information and actionable knowledge. Data mining is the computational process of discovering patterns in data sets involving methods at the intersection of artificial intelligence, machine...
Deep learning has revolutionised numerous fields in recent years. We've witnessed improvements in everything from computer vision through speech analysis to natural language processing as a result of the advent of massively parallel compute coupled with l...
Deep learning and differentiable programming has revolutionised numerous fields in recent years. We've witnessed improvements in everything from computer vision through speech analysis to natural language processing as a result of the advent of cheap GPGP...
Evolution by natural selection has created amazingly complex and sophisticated solutions to some very difficult problems - how exactly does it achieve this, and how can we harness this capability for engineering artificial systems and computational proble...
The last decade and a half have seen the Web move away from a purely document-centric information system to one in which hypertext techniques are applied to the sort of data found in databases; the term “Semantic Web” is used to refer to this Web of linke...
More and more people are using increasingly powerful mobile devices as their primary means of obtaining information and requesting services over the Internet. The shift from traditional personal computers (desktops and laptops) to mobile devices (Smart ph...
This module gives students an introduction to natural language processing (NLP) algorithms and an understanding of how to implement NLP applications.
This module is about the fundamentals of algorithms solving continuous optimisation problems, which involve minimising functions of multiple real-valued variables, possibly subject to restrictions, constraints, and nondifferentiable regularisations on the...
Computer Science has evolved significantly over the past decades, and various subfields require a strong foundation in probability. Such fondation is important in studying randomized algorithms, algorithm analysis, approximation algorithms and artificial ...
Simulation modelling plays an increasingly significant role across modern science and engineering, with the development of computational models becoming established practice in industry, consulting, and policy formulation. Computer scientists are often em...
The second generation of web sites that came along in the mid 2000's included many of the social media sites that are now household names (YouTube, Flickr, Wikipedia, Facebook, Blogger, Twitter, etc.) These sites (known at the time as Web 2.0) focused on ...
We teach most modules through a mixture of lectures, seminars and practical work.
We’ll work with you to improve your general knowledge of data science and develop your skills in:
You’ll also be able to choose between several diverse topics to suit your interests.
Depending on the modules that you take, we’ll assess your progress through a mixture of:
This is an opportunity to show your understanding of data science techniques and methods of enquiry. You will carry out a research project lasting 3 to 4 months, assessed by a 15,000-word dissertation
Your personal tutor is there to offer advice, help you choose modules, and provide general support if you need it. You can talk to your module tutors about any subject-specific questions. You’ll also be able to access the Electronics and Computer Science (ECS) Student Advisory Team for pastoral support.
Our graduates are sought after by:
We run a dedicated careers hub connected to over 100 organisations including:
We also support aspiring entrepreneurs through a blend of networks, mentors, societies and our on-campus start-up incubator. Find out more about enterprise and entrepreneurship opportunities.
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:
We have a thriving entrepreneurship culture. You'll be able to take advantage of:
Fees for a year's study:
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.
Your tuition fee covers the full cost of tuition and any exams. The fee you pay will remain the same each year from when you start studying this course. This includes if you suspend and return.
Find out how to pay your tuition fees.
Accommodation and living costs, such as travel and food, are not included in your tuition fees. There may also be extra costs for retake and professional exams.
Explore:
If you’re a graduate of the University of Southampton, you could be eligible for a 10% discount on your postgraduate tuition fees.
This can help with course fees and living costs while you study a postgraduate master's course. Find out if you're eligible.
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.
Find out about funding you could get as an international student.
For further details, read our step by step guide to postgraduate taught applications.
The deadline to apply for this course is Tuesday 9 September 2025, midday UK time.
We advise applying early as applications may close before the expected deadline if places are filled.
The deadline to apply for this course is Tuesday 26 August 2025, midday UK time.
We advise applying early as applications may close before the expected deadline if places are filled.
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.
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:
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.
You'll be able to track your application through our online Applicant Record System.
We receive a high volume of applications for this course. This means you may not receive a response to your application for up to 12 weeks.
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.
We treat and select everyone in line with our Equality and Diversity Statement.
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
