There has been a recent upsurge in commercial interest in the new role of "data scientist". This MSc (which can be studied part time or full time) , will prepare you to become an data scientist, a person who excels at manipulating and analysing data, particularly large data sets that don't fit easily into tabular structures (so-called "Big Data").
Why study this course at Dundee?
We have been working on 'big data' and data analysis for at least five years. We've also developed new algorithms and techniques for data scientists. We ran the most successful Business Intelligence Masters course in the UK and this course builds on that success.
Professor Mark Whitehorn and Andy Cobley will lead the course. Mark is an emeritus professor. He runs a successful consultancy company that specialises in BI, data sciences and analytics. Andy is the course organiser.
You will gain knowledge, skills and understanding of data science research and implementation. You will gain skills in professional procedures. This will ensure that your data science research and implementation is valid and actionable. You will then be able to debate about the role, ethics and utility of data science in commercial and other settings.
What is the difference between Data Science and Business Intelligence?
There is a huge overlap with Business Intelligence.
A BI specialist will need to understand data and data analytics. They have a bias towards understanding data storage in current enterprise operational systems. They may also design and install an analytical system, such as a data warehouse.
A data scientist will be less concerned with the design of a data warehouse. They will be more interested in the message the specific sets of data can deliver. They may find it difficult to interrogate data, for its secrets, without some understanding of data warehouses.
If you already have
- a strong grounding in Business Intelligence
- and would like to upgrade your knowledge to include topics from the Data Science MSc,
we offer the relevant Data Science modules either on a stand alone basis or as a PGCert.
The course is also available part time. This may suit you if you are already in employment and wish to take a MSc whilst still working full time.
What is so good about this course?
You will have 24-hour access to our award winning and purpose-built Queen Mother Building. It has an unusual mixture of lab space and breakout areas, with a range of conventional and special equipment for you to use. It's also easy to work on your own laptop as there is wireless access throughout the building. Our close ties to industry allows us access to facilities such as Windows Azure and Teradata, and university and industry standard software such as Tableau for you to evaluate and use.
The School of Computing maintains a friendly, intimate and supportive atmosphere, and we take pride in the fact that we know all of our students - you're far more than just a matriculation number to us. We have a thriving postgraduate department with regular seminars and guest speakers.
Who should study this course?
We are looking for students with:
- Insatiable curiosity
- Interdisciplinary interests
- Excellent communication skills
- Data Science (part time) MSc
- Data Science PGCert
- Data Science Individual Module
The programme will be delivered by Prof. Mark Whitehorn with input from Andy Cobley, Yasmeen Ahmad, Chris Hillman and other specialists from within the School of Computing in an innovative blend of live co-presented master-classes, video seminars and recorded materials. A series of guest speakers from industry will provide case studies across both semesters.
The programme will be provided predominantly on-campus, with two intensive study weeks in each of the semesters. Other classes may be taken off-campus using the university’s VLE, remote desktop, Adobe Connect and video conferencing systems along with telephone conferencing.
- Big Data - 20 Credits
- Business Intelligent Systems - 20 Credits
- Data Analysis and Visualisation - 20 Credits
- Analytical Database Models and Design - 20 Credits
- Advanced statistics and data mining - 20 credits
- MDX - 20 Credits
- Data Science Mini Project - 20 credits (for Certificate)
- Data Science Research Project - 60 credits
The PGCert is intended for students who have a strong grounding in Business Intelligence and would like to upgrade their knowledge to include topics from the Data Science MSc. The modules are available stand alone for those who want to take their time studying the material and perhaps build up to a PGCert.
The three modules that make up the PGCert are:
- Big Data
- Advanced Anlaysis
- Mini Project
For more information about the content of the course, please visit the course webpage on the School of Computing website.
Assessment will be by examination, practical coursework and research project.
Various job sites now report an increase in jobs carrying the title of data scientist. Other career opportunities are in intelligence analysis, data management/database maintenance, data processing manager, database development and research, business intelligence consultant and more.
Year of Entry: 2015
Entry Requirements: You should have, or expect to have, an honours degree at 2.1 or above, in Computing (or equivalent qualifications). However, if you don't meet this requirement you may still apply in which case you will need to prove that you have equivalent experience in the field in order to be accepted onto the course. All applicants will need to undergo a technical interview to ensure they have the necessary background to undertake the course.
EU and International students visit our EU and International webpages for entry requirements tailored to your home country.
English Language Requirement
Please check our English language requirements page for details of equivalent grades from other test providers, and information about the University of Dundee English language courses.
English Language Pre-Sessional Programmes
We offer Pre-Sessional programmes throughout the year and Foundation Programme(s) for both undergraduate and postgraduate students which start at the beginning of the academic year. These programmes are all designed to prepare you for university study in the UK when you have not yet met the language requirements for direct entry onto a degree programme. Successful completion of these programmes guarantees progression to various degrees at the University of Dundee as long as you hold a relevant offer.
The 30 week (one Academic Year) Foundation Programme(s) allow applicants who have not met our typical academic entry requirements, and require additional English Language support by up to 1.0 IELTS, to gain the necessary qualifications to enter the University of Dundee degree programmes in the following year.
The 24 week Pre-Sessional programme (March – August) provides additional English Language tuition for students who do not meet our minimum English Language requirements by up to 1.0 IELTS and the 10 week Pre-Sessional programme (June – August) (October – December) provides specialist English Language tuition for students who are 0.5 IELTS below the requirement for their degree programme.
There have been many changes to the arrangements for funding students entering higher education in recent years, yet a degree from the University of Dundee, with its high rate of employment success, remains a cost-effective option.
The fees you pay will depend on your fee status. Your fee status is determined by us using the information you provide on your application. Find out more about fee status.
|Fee status||Fees for students starting 2015/16|
|Scottish, Rest of UK and EU students||£7,200 per year of study
See our scholarships for UK/EU applicants
|Overseas students (non-EU)||£15,950 per year of study
See our scholarships for international applicants
For Data Science MSc
For Data Science (part-time) MSc
For Data Science PGCert
For Data Science Individual Module
Please read the Postgraduate "How to Apply" section for information on how to upload relevant documents to UKPASS before proceeding with your application.
Mr Andrew Cobley
School of Computing
+44 (0)1382 385078