Throughout the course, content is complemented by practical work, allowing you to support your theoretical knowledge with practical experience in data storage, mining, warehousing, visualisation and analysis as well as transferable skills.

*For students who undertake a placement the course duration will be extended by the length of the placement.

The individual project provides an opportunity for applying specialist knowledge together with analytic, problem-solving, managerial and communication skills to a particular area of interest within data science. Working with the full support and guidance of an allocated Project Supervisor, you will propose, plan, specify, develop, evaluate, and present a substantial project.

Graduate Stories

Read our Graduate Stories to find out more about the course:

Graduate Story - Karen Jewell - MSc Data Science

Graduate Story - Ludovico Lanni - MSc Data Science

Modules

Modules and delivery order may change for operational purposes. The University regularly reviews its courses. Course content and structure may change over time. See our

course and module disclaimer

for more information.

Detailed module information /n

Learning Methods

You will be taught through a mixture of lectures, tutorials, labs. You will be invited to attend talks presented by highly-experienced researchers, speakers from industry, and members of the BCS (British Computer Society) on a wide range of industry-related topics. You will also be supported through our online virtual learning environment where you can access a wide variety of resources and other support materials.

Part-time September start students

A) Part-time September start students who would like to work on their project during the summer start their project in May of their second year and complete in December of their third year.

(Approximately 28 months)

B) Part-time September start students who would like to avoid working on their project during the summer start their project in September of their third year and complete in May that year.

(Approximately 33 months)

Part-time January start students

C) Part-time January start students who would like to work on their project during the summer will start their project in January of their third year complete their project in August that year.

(Approximately 32 months)

D) Part-time January start students who would like to avoid working on their project during the summer will start their project in January of their third year, have a break during the summer term and continue their project September-December that year.

(Approximately 36 months)

How long is a Data Science course?

The MSc Data Science course can be successfully completed in:

12 - 17 months (full time)*

28 - 36 months (part time)

*For students who undertake a placement the course duration will be extended by the length of the placement.

Activity Summary

Lectures

- 30 students per group, 24 hours over two months

Tutorial

- 30 students per group, 24 hours over two months

Independent Study

A significant portion of this courses is underpinned by independent learning, and you will be expected to be responsible for managing your coursework, reading and other learning activities appropriately.

Assessment

Typically students are assessed each year:

Year 1

4 written exams, typically for 3-4 hours

2 reports

1 dissertation (final year project)

1 oral assessment

8 practical skills assessment

1 group critique

Feedback

We aim to provide you with feedback within 20 working days of hand-in for all written exams, coursework and practical exams.

Staff Delivering on this Course

Our staff members feature in the annual Support and Teaching staff with Appreciation and Recognition (STAR) awards voted by the students and organised by RGU:Union. Recently we have been awarded two Lecturer of the Year awards and an award for Continued Excellence.

Many of our academic staff are Fellows or Senior Fellows of the Higher Education Academy or are working towards this accolade. This is a professional recognition of practice, impact and leadership of teaching and learning.

Staff on this course could also include: visiting lecturers, visiting Distinguished Researchers, library staff and industry experts and postgraduate researchers.

Academic Support

The Inclusion Centre advises and supports students who disclose a sensory or mobility impairment, chronic medical condition, mental health issue, dyslexia and other specific learning differences. Applicants are encouraged to arrange a pre-entry visit to discuss any concerns and to view the facilities.

The Inclusion Centre

Online Learning & Support

All undergraduate and postgraduate students, whether you are learning on campus or by online learning, benefit from using our collaborative virtual learning environment, CampusMoodle. You will be provided with 24/7 online access to your learning material and resources, along with the ability to interact with your class members and tutors for discussion and support.

CampusMoodle

Study Skills Support

The Study Support Team provides training and support to all students in:

Academic writing

Study skills (note taking, exam techniques, time management, presentation)

Maths and statistics

English language

Information technology support

Study Skills Support

Library Support

The Library offers support for your course, including the books, eBooks, and journals you will need. We also offer online reading lists for many modules, workshops and drop-ins on searching skills and referencing, and much more.

University Library

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Placements

Students who perform particularly well during their first term of studies will be invited to apply for any long-term placement opportunities (40-45 weeks) found by the Placement Office. Alternatively, you can seek your own long placement or a short placement. Note that permission to undertake a placement is at the discretion of the School and students who go on long placement also need to pay a £1000 fee.

For students who undertake a placement the course duration will be extended by the length of the placement.

PLACEMENT OFFICE

Job Prospects

The opportunity to exploit Big Data is recognised world-wide, and it is included in government economic strategies. The UK Government and Scottish Governments highlight it as an emerging opportunity for growth. The course prepares you for a career in Data Science or in Big Data. Job openings include: Data Scientist, Data Analyst, Data Visualisation Specialist, Data Manager, Database Designer/Manager, Data Mining Expert and Big Data Scientist. The course also prepares students for research careers by providing the skills necessary of an effective researcher. Suitable MSc graduates may continue to PhD programmes within the school.

Aberdeen is home to many multinational oil and gas companies and associated suppliers such as mainstream software houses, IT providers to major oil-related companies, specialist software consultancies, and venture capital start-ups, so graduates can seek employment locally. RGU is also involved in a number of commercial collaborations on a local, national and international scale with organisations such as BP, British Geological Survey, Wood Group PSN, Accenture, WIPRO and many Aberdeen-based software development companies, and you may benefit from the university’s links with some of these companies when it comes to securing placements or employment.

CAREERS

PgCert | PgDip | MSc Data Science

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