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Data Engineering

MSc

The world is awash with data and much more is on the way, creating a tidal wave of Big Data. Data Engineers develop the infrastructure to store, manage, analyse this wave of data, to bridge the gap between Data and Computer Science. This unique course will give you the skills you’ll need to succeed as a Data Engineer.

Why study Data Engineering at Dundee?

The role of “Data Scientist” has been described as the “sexiest job of the 21st Century. However, there is a emerging a new role, that of Data Engineer as more companies are realising they need employees with specific skills to handle the amount of data that is being generated and the coming tidal wave from the Internet of Things.

This MSc has been created with industry input to prepare its students with the skills to handle this wave of data and to be at the forefront of its exploitation. Students on the sister programmes (“Data Science” and “Business Intelligence”) have gone on to work for some of the biggest companies in the industry and we are confident that graduates from this MSc will have the same success.

The School of Computing at the University of Dundee has been successfully offering related MSc programmes such as Business Intelligence and Data Science since 2010. These innovative programmes attract around 40 students per year, drawn from across Europe and Overseas.

What's so good about Data Engineering at Dundee?

Our facilities

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.

Postgraduate culture

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.

Special features

The University of Dundee has close ties with the Big Data industry, including Teradata, Datastax and Microsoft. We have worked with SAS, Outplay, Tag, GFI Max, BrightSolid and BIPB, and our students have enjoyed guest lectures from Big Data users such as O2, Sainsbury’s, M&S and IBM.

You will be able to work with a range of leading researchers and tutors, including top vision and imaging researchers and BI experts. Our honorary staff include legal experts, entrepreneurs and renowned industry experts such as John Richards of the newly formed IBM Watson Group.

Who should study this course?

We are looking for students with:

  • Insatiable curiosity
  • Interdisciplinary interests
  • Excellent communication skills

This course suits recent graduates in Computer Science (or related subjects) who wish to focus on data wrangling and the application of data analytics. Students should have a good grasp of Mathematics and a basic understanding of programming. Students with a scientific background will be considered if they can show that they have a relevant maths and computer background.

Related courses

Teaching & Assessment

This course is taught by staff in the School of Computing .

The start date is October and the course lasts for 12 months on a full time basis.

How you will be taught

The course will be taught by staff of the School of Computing. Depending on the modules you take this will include Andy Cobley, Professor Mark Whitehorn, and Professor Stephen McKenna.

What you will study

The course will be taught in 20 credit modules with a 60 credit dissertation. Students will require to complete 180 credits for the award of the MSc (including 60 credits for the dissertation). Students completing 120 credits (without the dissertation) will be eligible for a Postgraduate Diploma.

MSc

Semester 1
  • Introduction to Data Mining and Machine Learning part 1
  • Programming Languages for Data Engineering part 1
  • Big Data
  • Computer Vision
Semester 2
  • Introduction to Data Mining and Machine Learning part 2
  • Programming Languages for Data Engineering part 2
  • Business Intelligence Systems

Options:

  • Transactional Database Systems
  • Research Methods
Semester 3
  • Research project with optional industrial collaboration
Course content

Each module on the course is designed to give the student the skills and understanding they need to succeed in the Data Engineering/ Science field. Content on the course includes (but is not limited to):

  • CAP theorem
  • Lamda Architecture
  • Cassandra, Neo4j and other nosql databases
  • The Storm distributed real time computation system
  • Hadoop, HDFS, MapReduce, and other Hadoop/SQL technologies
  • Spark and Shark frameworks
  • Data Engineering languages such as Python, erlang, R, Matlab
  • Vision systems, which are becoming increasingly important in data engineering for extracting features from large quantities of images such as from traffic, medical and industrial
  • RDBMS systems which will continue to play an important role in data handing and storage. You will be expected to research the history of RDMBS and delve in to the internals of modern systems
  • OLAP cubes and Business Intelligence systems, which can be the best and quickest way to extract information from data stores
  • Goals of machine learning and data mining
  • Clustering: K-means, mixture models, hierarchical
  • Dimensionality reduction and visualisation
  • Inference: Bayes, MCMC
  • Perceptrons, logistic regression, neural networks
  • Max-margin methods (SVMs)
  • Mining association rules
  • Bayesian networks

How you will be assessed

The course is assessed through a combination of examinations, coursework, presentations and interviews. Each module is different: for instance the Big data module has 40% coursework, consisting of Erlang programming and a presentation on nosql databases, along with an examination worth 60%.

Careers

Our experience suggests that graduates of this course will have most impact in the following areas:

  • Cloud and web based industries that handle large volumes of fast moving data that need to be stored, analysed and maintained. Examples include the publishing industry (paper, TV and internet), messaging services, data aggregators and advertising services
  • Internet of Things. A large amount of data is being generated by devices (robotic assembly lines, home power management, sensors etc.) all of which needs to be stored and analysed.
  • Health. The NHS (and others) are starting to store and analyse patient data on an unprecedented scale. The healthcare industry is also combining data sources from a large number of databases to improve patient well-being and health outcomes
  • Games industry. The games industry records an extraordinary amount of data about its customers' play activities, all of which needs to be stored and analysed. This course will equip students with the knowledge and skill to engage with the industry

Entry Requirements

EU and International students visit our EU and International webpages for entry requirements tailored to your home country.

Applicants should normally have an Honours degree at 2.1 level or above in computing or a related subject. All prospective students need to undergo a technical interview to ensure they have the necessary background knowledge, including Mathematics, to undertake the course.

English Language Requirement

IELTS of 6.0 (or equivalent), if your first language is not English. Please check our 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.

Fees and Funding

Academic Year Home/EU Overseas
2014-15
(inc Jan 2015)
£3,800 £13,250

Sources of Funding

Information about the School of Computing scholarships can be found on the School of Computing scholarships webpage.

Other sources of funding for postgraduate students can be found on our Scholarships webpage.

Living Costs

  • Dundee is ranked as one of the most affordable places for students to live in the UK, and the cost of living is around 15% cheaper than the UK average.
  • Increasing numbers of students are successfully undertaking part-time work to supplement their income. You can get advice from our Careers Service, both about job opportunities and how to find a suitable study/work/life balance. EU and international students are also allowed to work up to 20 hours per week.
  • As a student in Scotland, you have free access to the National Health Service. Visits to doctors and hospitals, as well as prescriptions, sight tests and dental checkups, are available free of charge.

Your Application

Apply online via UKPASS

You must read the information regarding how to upload relevant documents to UKPASS before proceeding with your application.

Applications for this course are not yet open. Please register your interest and we will let you know when you are able to apply.

Programme Director

Mr Andy Cobley
School of Computing
University of Dundee
Nethergate
Dundee
DD1 4HN
Scotland

Telephone: 01382 385078 (from the UK)
Telephone: +44 1382 385078 (from outside the UK)

Fax: 01382 385509 (from the UK)
Fax: +44 1382 385509 (from outside the UK)

Email: aecobley@computing.dundee.ac.uk

Admissions Contact

Postgraduate Admissions
Admissions and Student Recruitment
University of Dundee
Nethergate
Dundee
DD1 4HN
Scotland

Telephone: 01382 384 384 (from the UK)
Telephone: +44 1382 384 384 (from outside the UK)

Fax: 01382 385 500 (from the UK)
Fax: +44 1382 385 500 (from outside the UK)

Email: postgrad-admissions@dundee.ac.uk