About this course
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:
- intelligent agents
- computational finance
- open data innovation
- the science of online social networks
- deep learning
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.
Your course leader specialises in database systems research, with a focus on using data appropriately and effectively. Visit Dr Age Chapman’s staff profile to learn more about her work.
MSc Data Science at the University of Southampton
This course is based at Highfield.
This qualification is awarded by the University of Southampton.
Download the programme specification
The programme specification sets out the learning outcomes of this course and details how the course is taught and assessed.
You’ll need an upper 2:1 degree in one of the following subjects:
- computer science
- computer engineering
- software engineering
You must also have an upper 2:1 score in the following modules:
- a programming module (e.g. MATLAB, Python, Java, C, C++, C#)
- an advanced maths module, ideally statistics and probability
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
We accept other English language tests. Find out which English language tests we accept.
Got a question?
Please contact us if you're not sure you have the right experience or qualifications to get onto this course.
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.
For entry in Academic Year 2021-22
Year 1 modules
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.
- To introduce key concepts in pattern recognition and machine learning; including specific algorithms for classification, regression, clustering and probabilistic modeling. - To give a broad view of the general issues arising in the application of algor...
Increasing numbers and kinds of computationally-driven systems require engagement with human beings. While some examples are obvious, from apps to social media to social computing, some are perhaps less obvious such as secure systems, autonomous vehicles,...
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 cheap GPGPU compute coupled with large da...
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...
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...
Open data, pitched as the raw material of the new industrial revolution, holds great promise, but how do you exploit this new resource? This course is specifically designed to give students a greater understanding on how to innovate with open data. This ...
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...
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 ...
Learning and assessment
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:
- using high-performance computing clusters
- working with cloud-based infrastructure
- devising and applying Big Data analytics techniques
- analysing data with machine learning tools
- creating data visualizations to communicate information
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:
- lab reports
- problem solving exercises
- design and programming exercises
- individual and group projects
- your compulsory dissertation
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:
- companies looking for trends in sales, marketing or operational data
- start-ups pursuing new opportunities in big data
- government departments using linked open data to inform policy
- research/consultancy companies analysing data on behalf of their clients
- academic organisations with opportunities for doctoral study
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.
Careers services at Southampton
We're a top 20 UK university for employability (QS Graduate Employability Rankings 2020). Our Careers and Employability Service 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:
Fees, costs and funding
Fees for a year's study:
- UK students pay £9,250.
- EU and international students pay £26,850.
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 get 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.
Funding your postgraduate studies
A variety of additional scholarships, grants and bursaries may be available to help you fund your master’s study, both from the University and from 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.
We receive a high volume of applications for this programme. So that we can guarantee a good quality of service and select the most able students, we operate admissions in stages.
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.
|Stage:||Applications open:||Deadline for applications (midnight):||Decisions back to applicants by (5pm):|
Monday 19 October 2020
Thursday 12 November 2020
Friday 18 December 2020
Friday 20 November 2020
Thursday 14 January 2021
Friday 19 February 2021
Friday 22 January 2021
Thursday 18 March 2021
Friday 23 April 2021
Friday 26 March 2021
International applicants: Thursday 20 May 2021
International applicants: Friday 25 June 2021*
* If you are an international applicant who requires a visa to study in the UK, you will need to allow enough time to apply for and receive your visa before our induction events from 27 September 2021. If we are able to make enough offers to fill all places on the programme in any stage, we may not open the programme in later stages.
Application assessment fee
We’ll ask you to pay a £50 application assessment fee if you’re applying for any postgraduate taught course that starts in or after September 2021.
This is an extra one-off charge which is separate to your tuition fees. 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 a Master of Research (MRes) degree, you will not need to pay the fee. 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:
- your knowledge of the subject area
- why you want to study a postgraduate qualification in this course
- how you intend to use your qualification
You'll also need to send 2 academic references.
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.
Learn more about how to apply with our postgraduate application guide.
What happens after you apply
You'll be able to track your application through our online Applicant Record System.
We'll assess your application on the strength of your:
- academic achievements
- relevant professional experience
- personal statement
- academic references
We'll usually make one of 4 decisions:
- Offer you a place on this course
- Offer you a place on a different course which we think suits you better
- Tell you that we'll consider your application a second time in the next stage
- Tell you that your application has been unsuccessful
If we decide to consider your application a second time in the next stage, this will only happen once.
If we offer you a place, you'll need to accept the offer within 30 working days. If you do not meet this deadline, we'll offer your place to another applicant.
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.
Tel: +44(0)23 8059 5000
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