Edinburgh: Extraordinary futures await.

Data Science, Technology and Innovation (Online Learning) MSc, PgDip (ICL), PgCert (ICL), PgProfDev

Awards: MSc, PgDip (ICL), PgCert (ICL), PgProfDev

Study modes: Part-time Intermittent Study, Full-time

Online learning

Funding opportunities

Participation in the DSTI programme has significantly expanded my knowledge of data science and latest technologies. This has enabled me to lead an inspiring team and very quickly build an innovative analytics platform which implements machine learning concepts.

Maggie Paruch

Demand is growing for high value data specialists across the sciences, medicine, arts and humanities. The aim of this unique, modular, online distance learning programme is to enhance existing career paths with an additional dimension in data science.

The programme is designed to fully equip tomorrow’s data professionals, offering different entry points into the world of data science – across the sciences, medicine, arts and humanities.

Students will develop a strong knowledge foundation of specific disciplines as well as direction in technology, concentrating on the practical application of data research in the real world.

Our online learning technology is fully interactive, award-winning and enables you to communicate with our highly qualified teaching staff from the comfort of your own home or workplace.

Our online students not only have access to the University of Edinburgh’s excellent resources, but also become part of a supportive online community, bringing together students and tutors from around the world.

Studying online at Edinburgh

Find out more about the benefits and practicalities of studying for an online degree:

You can study to the following levels:

  • MSc
  • Postgraduate Diploma
  • Postgraduate Certificate
  • Postgraduate Professional Development (PPD)

PPD credits will be recognised in their own right for postgraduate level credits or may be put towards gaining a higher award such as a PgCert, Diploma or MSc.

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 Science, Technology and InnovationUp to 6 YearsPart-time Intermittent StudyProgramme structure 2024/25
MScData Science, Technology and Innovation1 YearFull-timeProgramme structure 2024/25
PgDip (ICL)Data Science, Technology and InnovationUp to 4 YearsPart-time Intermittent StudyProgramme structure 2024/25
PgCert (ICL)Data Science, Technology and InnovationUp to 2 YearsPart-time Intermittent StudyProgramme structure 2024/25

The modular course structure offers broad engagement at different career stages. Individual courses provide an understanding of modern data-intensive approaches while the programme provides the knowledge base to develop a career that majors in data science in an applied domain.

This programme is intended for professionals wishing to develop an awareness of applications and implications of data intensive systems. Our aim is to enhance existing career paths with an additional dimension in data science, through new technological skills and/or better ability to engage with data in target domains of application.

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.

The programme is designed to be accessible. We welcome applicants who meet the standard academic entrance requirements and those with relevant work experience.

A UK 2:1 honours degree, or its international equivalent.

We will also consider a UK 2:2 honours degree, or its international equivalent, in Computer Science, Informatics, Software Engineering, Computational Physics, Mathematical Physics, Mathematics, Statistics, Computational Chemistry, Chemistry with Computer Science, Physics with Computer Science, or Computational Biology.

All applicants need to have some understanding of basic computer programming concepts. If your undergraduate degree discipline is not listed above, you must highlight on your application any relevant knowledge/experience.

We will also consider your application if you have relevant work experience. If you plan to apply on this basis, please include a detailed CV and outline how your professional background demonstrates your ability to undertake the programme in the Relevant Knowledge/Training section of your application. If you are unsure if you have relevant work experience, please email the Data Science team. You may be admitted to the Postgraduate Professional Development route in the first instance.

We strongly recommend that all applicants have SQA Higher or GCE A level Mathematics, or equivalent, and ideally some mathematics classes taken at undergraduate level. We also recommend that students have some experience of computer programming (e.g. C, Fortran, Java, Python, R).

Students from China

This degree is Band C.

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 6.5 with at least 6.0 in each component. We do not accept IELTS One Skill Retake to meet our English language requirements.
  • TOEFL-iBT (including Home Edition): total 92 with at least 20 in each component. We do not accept TOEFL MyBest Score to meet our English language requirements.
  • C1 Advanced (CAE) / C2 Proficiency (CPE): total 176 with at least 169 in each component.
  • Trinity ISE: ISE II with distinctions in all four components.
  • PTE Academic: total 65 with at least 59 in each component. We do not accept PTE Academic Online.
  • Oxford ELLT: 7 overall with at least 6 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:

Details can be found in the course descriptors within the programme codes listed above in Programme Structure.

Tuition fees

AwardTitleDurationStudy mode
MScData Science, Technology and InnovationUp to 6 YearsPart-time Intermittent StudyTuition fees
MScData Science, Technology and Innovation1 YearFull-timeTuition fees
PgDip (ICL)Data Science, Technology and InnovationUp to 4 YearsPart-time Intermittent StudyTuition fees
PgCert (ICL)Data Science, Technology and InnovationUp to 2 YearsPart-time Intermittent StudyTuition fees
PgProfDevData Science, Technology and InnovationUp to 2 YearsPart-time Intermittent StudyTuition 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

Featured funding

Search for scholarships and funding opportunities:

  • Bayes Centre
  • The University of Edinburgh
  • 47 Potterrow
  • Central Campus
  • Edinburgh
  • EH8 9BT

You must apply at least one month prior to the start date of the programme so that we have enough time to process your application. If you are also applying for funding then we strongly recommend you apply as early as possible.

You must submit one reference with your application.

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

Further information

  • Bayes Centre
  • The University of Edinburgh
  • 47 Potterrow
  • Central Campus
  • Edinburgh
  • EH8 9BT