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MSc Data Science

Course Description

There has been a recent upsurge in commercial interest in the new role of "data scientist". A data scientist is 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 Data Science at Dundee?

The School of Computing has been working on 'big data' and data analysis for at least five years; not only working with data but also developing new algorithms and techniques for data scientists. The School already runs the most successful Business Intelligence Masters course in the UK.

This course will be led by Professor Mark Whitehorn and Andy Cobley. Mark is an emeritus professor at the University of Dundee and also runs a successful consultancy company that specialises in BI, Data Sciences and analytics. Andy is the course organiser for both the existing BI course and the new Data Science course.

This course will enhance your employability by providing you with knowledge, skills and understanding of data science research and implementation. You will also acquire skills in the professional procedures necessary to ensure that data science research and implementation is both valid and actionable and engage with contemporary 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 clearly a huge overlap with Business Intelligence. A BI specialist will need to understand data and data analytics. However there is a bias towards understanding how data is stored in the current operational systems within an enterprise the design and the implementation of an analytical system such as a data warehouse. A data scientist will be less concerned with the construction of a data warehouse and more interested in the message the specific sets of data can deliver.

However, without some understanding of data warehouses the data scientist will find it difficult to interrogate the data for its secrets. For this reason there is overlap between the two courses.

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.

What's so good about Data Science at Dundee?

Our facilities will give you 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.

A booming Postgraduate culture where 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.

Duncan Ross (Director of Data Sciences at Teradata) has said that: "The first and most important trait is curiosity. Insane curiosity. In many walks of life evolution selects against the kind of person who decides to find out what happens 'if I push that button'. Data Science selects for it."

How you will be taught

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.

What you will study

Semester 1
Big Data - 20 Credits
Business Intelligent Systems - 20 Credits
Data Analysis and Visualisation - 20 Credits

Semester 2
Analytical Database Models and Design - 20 Credits
Advanced statistics and data mining - 20 credits
MDX - 20 Credits

Semester 3
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.

How you will be assessed

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.

Visit the MSc Data Science page on the University of Dundee website for more details!

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.

Course Fees

UK/EU 2016-2017 £7,200 OS 2016-2017 £15,950. For Partime/individual see course Description.

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