Postgraduate study

Data Science

Awards: MSc

Study modes: Full-time, Part-time

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; and separate research areas have grown around different types of unstructured data such as text, images, sensor data, video, and speech.

You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.

Compulsory courses

  • Informatics Research Review
  • Informatics Project Proposal
  • Dissertation

You are also required to take a breadth of courses in data science, with at least one in each of the following areas:

  • Machine Learning, Statistics and Optimization
  • Databases and Data Management
  • Applications

You can take up to two courses from other schools.

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 2017/18
MScData Science2 YearsPart-timeProgramme structure 2017/18
MScData Science3 YearsPart-timeProgramme structure 2017/18

The School of Informatics' MSc in Data Science is designed to attract 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 such as in our CDT in Data Science.

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.

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.

You should have experience of computer programming equivalent to an introductory programming course and have completed the equivalent to 60 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 (eg. Induction and reasoning, Graph theoretic models, proofs), and Probability (concepts in discrete and continuous probabilities, Markov Chains etc. )

International qualifications

Check whether your international qualifications meet our general entry requirements:

English language requirements

All applicants must have one of the following qualifications as evidence of their English language ability:

  • an undergraduate or masters degree, that was taught and assessed in English in a majority English speaking country as defined by UK Visas and Immigration

  • IELTS Academic: total 6.5 with at least 6.0 in each component
  • TOEFL-iBT: total 92 with at least 20 in each section
  • PTE(A): total 61 with at least 56 in each of the Communicative Skills scores
  • CAE and CPE: total 176 with at least 169 in each paper
  • Trinity ISE: ISE II with distinctions in all four components

Degrees taught and assessed in English must be no more than two and a half years old at the beginning of your degree programme. Language tests must be no more than two years old at the beginning of your degree programme.

Find out more about our language requirements:

Applicants receiving an offer of admission, either unconditional or conditional, will be asked to pay a tuition fee deposit of £1,500 to secure their place on the programme by 31st March.

Any applicants who are required to pay will receive an offer with full details. If there is no information on your offer about the deposit you are not required to pay. The deposit has to be paid by 31st March for offers made by 1st March, within 28 days for offers made before 30th June and within 14 days for those offers made from 1st July onwards.

Find out more about tuition fees and studying costs:

  • School of Informatics Teaching Organisation
  • 6th Floor, Appleton Tower
  • Central Campus
  • Edinburgh
  • EH8 9LE

We encourage you to apply at least one month prior to entry so that we have enough time to process your application. If you are also applying for funding or will require a visa then we strongly recommend you apply as early as possible. We may consider late applications if we have places available, but you should contact the relevant Admissions Office for advice first.

You must submit a reference with your application.

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

Further information

  • School of Informatics Teaching Organisation
  • 6th Floor, Appleton Tower
  • Central Campus
  • Edinburgh
  • EH8 9LE