Learning, teaching and assessment methods focus on providing students with engaging and contemporary materials that link theory to practice and require students to take a critical perspective on both. By linking learning and development directly to work activities, students can ensure that their professional development is part of the strategic aims of the organisation. Students will also have the opportunity to consider and reflect on established views of the organisation and processes relating to Data Science, in order to promote innovation and change.
What you'll study
For the award of MSc you must successfully pass all five modules, giving a total of 180 credits. All modules are 20 credits, except where indicated.
Work based learning (Advanced Professional Practice Module) - 60 credits
You’ll be mentored and supported by a dedicated team with both academic and industry experience to deliver a package of Data Science related work over three trimesters drawing on your current projects/activities in your workplace. Your employer is required to provide support, and to give permission for you to use for academic credit purposes a project (or series of related projects) within your workplace, which are part of your planned work activity and undertaken during normal working hours.
Three modules (one per trimester)
- Data Driven Decision making
- Data Analytics
- Data Wrangling
Software and technologies used will include packages such as: R, Python, Hadoop, Weka, Tableau.
MSc Dissertation - 60 credits
Your final project will allow you to use the tools and approaches you’ve developed on the course.
Study modules mentioned above are indicative only. Some changes may occur between now and the time that you study.
Full information on this is available in our disclaimer.
We encourage you to submit your application for September 2018 entry by 31st July 2018.
The entry requirement for this course is a Bachelor (Honours) Degree at a 2:2 or above in an appropriate field, for example, software development, computing, or business analytics. Alternatively, other qualifications or experience that demonstrate through our recognition of prior learning process that you have appropriate knowledge and skills at SCQF level 10 may be considered.
Applicants will be expected to be working in a role related to data analytics, whether in a technical or business context and will be required to provide a letter of support from their employer. Some experience of associated technologies such as databases, software development and related tools is assumed.
English language requirements
If your first language isn't English, you'll normally need to undertake an approved English language test and our minimum English language requirements will apply.
This may not apply if you have completed all your school qualifications in English, or your undergraduate degree was taught and examined in English (within two years of starting your postgraduate course). Check our country pages
to find out if this applies to you.
Our entry requirements indicate the minimum qualifications with which we normally accept students. Competition for places varies from year to year and you aren't guaranteed a place if you meet the minimum qualifications.
If your qualifications aren't listed above, visit our country pages to get entry requirements for your country.
Please note that non-EU international students are unable to enrol onto the following courses:
BN Nursing/MN Nursing (Adult, Child, Mental Health or Learning Disability)
BM Midwifery/MM Midwifery
We are committed to being as accessible as possible to anyone who wants to achieve higher education.
Our admissions policies will help you understand our admissions procedures and how decisions are made.