Postgraduate study
Edinburgh: Extraordinary futures await.

Data Science MSc

Awards: MSc

Study modes: Full-time, Part-time

Funding opportunities

Programme website: Data Science

Data science is the study of the computational principles, methods, and systems for extracting and structuring knowledge from data; and the application and use of those principles. Large data sets are now generated by almost every activity in science, society, and commerce - ranging from molecular biology to social media, from sustainable energy to health care.

As an MSc Data Science student, you will explore how to efficiently find patterns in these vast streams of data. Many research areas have tackled parts of this problem:

  • Machine learning focuses on finding patterns and making predictions from data.
  • Ideas from algorithms and databases are required to build systems that scale to big data streams.
  • Separate research areas have grown around different types of unstructured data such as text, images, sensor data, video, and speech.

Reputation

The University of Edinburgh consistently ranks top 30 globally for Computer Science.

The Research Excellence Framework (REF) 2021 ranked our School 1st in the UK for research power in Computer Science and Informatics. This means you will learn from experts at the forefront of their fields, undertaking cutting-edge research in a wide range of areas.

Environment

You will be part of a large, vibrant department with around 1,750 students across undergraduate, master’s and research programmes and 150 academic staff.

You will study in the heart of Edinburgh city centre, regularly voted as one of the most desirable places to live in the world, and one of the UK’s fastest-growing tech hubs.

You will follow two taught semesters of lectures, tutorials, project work and written assignments (September to May). During this time you will also learn research methods (such as literature review and project planning) to prepare for your final project and dissertation, which is completed during the summer.

Courses

You are required to take a breadth of courses in data science, with at least one in each of the following areas (examples of courses recently offered in each area are listed in parentheses):

  • Machine Learning, Statistics and Optimization (e.g., Machine Learning and Pattern Recognition, Statistical Programming, Large Scale Optimization for Data Science)
  • Databases and Data Management (e.g., Introduction to Databases, Extreme Computing, Advanced Database Systems)
  • Applications (e.g., Text Technologies for Data Science, Accelerated Natural Language Processing, Image and Vision Computing)

Project

The project is an essential component of the master's degree. It is a substantial piece of full-time independent work supervised by a member of teaching staff.

You will have prepared for your research project in semester 2. The project is undertaken over the summer months, culminating in the submission of a dissertation.

Students typically choose from a wide range of projects proposed by our academic staff. Students who are sponsored by or have close contact with an industrial company may wish to undertake a project which relates to that company’s activities. Students who self-propose topics (including those in conjunction with industry) must find an interested supervisor from the School of Informatics.

Part-time study

Those studying the 2-year part-time option take half of the taught credits in their first year, and the other half in the second year, followed by full-time work on the final project in the summer at the end of the second year.

There is also a 3-year part-time option which spreads the final project over a third year.

Both options require flexibility during the semesters: our large course offering means that taught courses have contact times at irregular hours throughout the whole week.

Delivery

This is an in-person programme, and we expect you to be in Edinburgh.

Courses are taught on campus, both full-time and part-time, during teaching hours (currently 9am-7pm) Monday – Friday. To succeed, you will need to maintain a consistent level of study each week.

Students are expected to stay in Edinburgh for the duration of their degree programme. This includes during the writing of the dissertation until the submission deadline.

Find out more about compulsory and optional courses

We link to the latest information available. Please note that this may be for a previous academic year and should be considered indicative.

Find out more about compulsory and optional courses

We link to the latest information available. Please note that this may be for a previous academic year and should be considered indicative.

AwardTitleDurationStudy mode
MScData Science1 YearFull-timeProgramme structure 2024/25
MScData Science2 YearsPart-timeProgramme structure 2024/25
MScData Science3 YearsPart-timeProgramme structure 2024/25

The School of Informatics' MSc in Data Science is designed for students who want to establish a career as a data scientist in industry or the public sector, as well as students who want to explore the area prior to further training or research.

The learning objectives of the degree are to foster:

  • a breadth of knowledge across the data science areas
  • an advanced technical background in at least one of the data science areas
  • an appreciation for real-world problems involving the use of data in industry, science, and the public sector
  • research experience in one of the data science areas

You will develop specialist, advanced skills in data science methods and their applications.

You will gain practical experience and a thorough theoretical understanding of the field, making you attractive to a wide range of employers or preparing you for further academic study.

Start-ups and spinouts

The University of Edinburgh has a long track record of start up companies and innovations, including key players in the industry set up by Informatics master’s alumni:

  • FanDuel, a unicorn company
  • Robotical
  • RISE Nutrition
  • Carbon Glance
  • Predictiva

Edinburgh Innovations – start-up opportunities

We have fantastic resources through the University’s commercialisation service, Edinburgh Innovations, to help you successfully nurture your entrepreneurial ideas and launch your own enterprise.

Career development through societies

Our active student societies, such as CompSoc and Hoppers, offer skills building, networking and industry events.

Recent speakers include:

  • Spotify
  • Amazon
  • Meta

Find out more about CompSoc and Hoppers:

Careers Service

Our award-winning Careers Service plays an essential part in your wider student experience at the University, providing:

  • tailored advice
  • individual guidance and personal assistance
  • internships and networking opportunities (with employers from local organisations to top multinationals)
  • Events such as the annual Careers in Tech and Data Fair, giving you opportunities to meet recruiters actively looking to recruit our students
  • access to the experience of our worldwide alumni network

We invest in your future beyond the end of your degree. Studying at the University of Edinburgh will lay the foundations for your future success, whatever shape that takes.

Hear from our Alumni

You will be based in the School of Informatics’ main teaching building, Appleton Tower. The building provides purpose-built facilities and dedicated learning and teaching spaces, all located in the University's Central Area.

IT facilities include computer labs with more than 250 high-spec machines and comprehensive support provided by dedicated computing staff.

In the project phase you will also have access to Appleton Tower's floor 9 (accessed only by master's students at this time) which has computing labs, private study spaces and beautiful panoramic views across Edinburgh.

The Informatics Student Experience Team is based within the Student Services in Appleton Tower.

If you take courses from other Schools, these might be delivered in the Nucleus building, on the University's Kings Buildings Campus.

You will have access to the University's facilities across all University sites.

For example:

  • libraries
  • study spaces (some of which are open 24 hours)
  • computing facilities
  • social spaces
  • leisure facilities

Student Adviser

All students have a named Student Adviser who you can visit in Appleton Tower. The team provide general support and guidance to students who are encountering difficulties with any aspect of University life.

Where appropriate they will liaise with other University Support Services, so they are able to provide the best possible support and advice for you. They can also help with a wide range of administrative and practical issues to do with your degree programme.

Take a virtual tour

Take a closer look at all our facilities on the University’s Virtual Visit site:

These entry requirements are for the 2025/26 academic year and requirements for future academic years may differ. Entry requirements for the 2026/27 academic year will be published on 1 Oct 2025.

A UK 2:1 honours degree, or its international equivalent, in informatics, artificial intelligence, cognitive science, computer science, electrical engineering, linguistics, mathematics, philosophy, physics, psychology or another quantitative discipline.

Entry to this programme is competitive. A typical offer will normally require a UK first class honours degree.

You should have experience of computer programming equivalent to an introductory programming course and have completed the equivalent of 60 SCQF credits or 30 ECTS credits of mathematics during your degree that have typically covered the following subjects/topics: calculus (differentiation and integration), linear algebra (vectors and multi-dimensional matrices), discrete mathematics and mathematical reasoning (e.g. induction and reasoning, graph theoretic models, proofs), and probability (concepts in discrete and continuous probabilities, Markov chains etc.)

Students from China

This degree is Band B.

International qualifications

Check whether your international qualifications meet our general entry requirements:

English language requirements

Regardless of your nationality or country of residence, you must demonstrate a level of English language competency which will enable you to succeed in your studies.

English language tests

We accept the following English language qualifications at the grades specified:

  • IELTS Academic: total 7.0 with at least 6.5 in each component. We do not accept IELTS One Skill Retake to meet our English language requirements.
  • TOEFL-iBT (including Home Edition): total 100 with at least 23 in each component. We do not accept TOEFL MyBest Score to meet our English language requirements.
  • C1 Advanced (CAE) / C2 Proficiency (CPE): total 185 with at least 176 in each component.
  • Trinity ISE: ISE III with passes in all four components.
  • PTE Academic: total 73 with at least 65 in each component. We do not accept PTE Academic Online.
  • Oxford ELLT: 8 overall with at least 7 in each component.

Your English language qualification must be no more than three and a half years old from the start date of the programme you are applying to study, unless you are using IELTS, TOEFL, Trinity ISE or PTE, in which case it must be no more than two years old.

Degrees taught and assessed in English

We also accept an undergraduate or postgraduate degree that has been taught and assessed in English in a majority English speaking country, as defined by UK Visas and Immigration:

We also accept a degree that has been taught and assessed in English from a university on our list of approved universities in non-majority English speaking countries (non-MESC).

If you are not a national of a majority English speaking country, then your degree must be no more than five years old at the beginning of your programme of study.

Find out more about our language requirements:

Deposit

If you receive an offer of admission you will need to pay a deposit to secure your place.

  • £1,500 (this contributes towards your tuition fees)

Find out more about tuition fee deposits:

Tuition fees

AwardTitleDurationStudy mode
MScData Science1 YearFull-timeTuition fees
MScData Science2 YearsPart-timeTuition fees
MScData Science3 YearsPart-timeTuition fees

Funding for postgraduate study is different to undergraduate study, and many students need to combine funding sources to pay for their studies.

Most students use a combination of the following funding to pay their tuition fees and living costs:

  • borrowing money

    • taking out a loan

    • family support

  • personal savings

  • income from work

  • employer sponsorship

  • scholarships

Explore sources of funding for postgraduate study

Scholarships and student funding

You can find funding opportunities, tuition fees and costs of living for prospective UK and international postgraduate students on the University website.

You are also encouraged to undertake your own research into the range of potential scholarships and other funding outside the University for which you may be eligible.

Search for scholarships and funding opportunities:

  • School of Informatics
  • 11 Crichton Street
  • Central Campus
  • Edinburgh
  • EH8 9LE
Programme start date Application deadline
8 September 2025 31 March 2025

Due to high demand on our programmes, the School of Informatics operates an application deadline of 31 March.

We will make a small number of offers to the most outstanding candidates on an ongoing basis, but will hold the majority of applications until the advertised deadline.

Decisions will be made as soon as possible once the deadline has passed. We expect to make the majority of decisions within eight weeks of the deadline.

The deadline may be extended if there are any places remaining on the programme.

Selection Deadlines

Application Deadline Expected Decision date
31 March 31 May

You must submit one reference with your application.

Find out more about the general application process for postgraduate programmes:

Further information

  • School of Informatics
  • 11 Crichton Street
  • Central Campus
  • Edinburgh
  • EH8 9LE