Taught course

Data Science

Institution
University of Glasgow · School of Computing Science
Qualifications
MScPGDip

Entry requirements

A minimum of a 2.1 Honours degree or equivalent (eg GPA 3.0 or equivalent) with computing as a major subject. Further information regarding academic entry requirements: student.recruitment@glasgow.ac.uk

Months of entry

September

Course content

The Masters in Data Science provides you with a thorough grounding in the analysis and use of large data sets, preparing you for responsible positions in the Big Data and IT industries. As well as studying a range of taught courses reflecting the state-of-the-art and the expertise of our internationally respected academic staff, you will undertake a significant programming team project, and develop your own skills in creating a project proposal and in conducting a data science project.

Why Glasgow?

· The University of Glasgow’s School of Computing Science is consistently highly ranked achieving 1st in Scotland and 2nd in the UK (Guardian University Guide 2014)

· The School is a member of the Scottish Informatics and Computer Science Alliance: SICSA. This collaboration of Scottish universities aims to develop Scotland's place as a world leader in Informatics and Computer Science research and education.

· With a 97% overall student satisfaction in the National Student Survey 2014, the School of Computing Science continues to meet student expectations combining both teaching excellence and a supportive learning environment.

· You will have opportunities to meet industrial speakers who contribute to our professional skills & issues course. Employers also come to make recruitment presentations, and often seek to recruit our graduates during the programme.

· You will benefit from having 24-hour access to a computer laboratory equipped with state-of-the-art hardware and software.

Programme Structure

Modes of delivery of the MSc in Data Science include lectures, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.

Core courses

· Big data

· Distributed algorithms and systems

· Information retrieval

· Machine learning

· Professional skills and issues

· Research methods and techniques

· Masters team project.

Optional courses

· Advanced operating systems

· Artificial intelligence

· Component-based software engineering

· Computer architecture

· Computer vision methods and applications

· Constraint programming

· Cyber security

· Enterprise computing

· Financial software engineering

· Functional programming

· Human computer interaction

· Human computer interaction: design and evaluation

· Human-centred security

· Information technology architecture

· Mobile human computer interaction

· Multimedia systems and applications

· Safety critical systems

· Trends in information security

Depending on staff availability, the optional courses listed here may change.

Projects

· To complete the MSc degree you must undertake a project worth 60 credits. This is a project chosen by you to investigate a challenging but constrained Data Science problem.

· The project will integrate the subject knowledge and generic skills that you will acquire during your Masters.

· We offer a wide range of projects, and each student is normally allocated a different project. We take your preferences into account when we allocate the projects.

· You will also have the opportunity to propose your own project, subject to academic approval.

Here are some typical project titles:

· Big Data modern database showdown

· Support for PBS batch jobs in Hadoop 2.0

· Real-time corroboration of information from Twitter using follower graphs

· A Hybrid Learning to Rank Approach for an Effective Web Search Engine

· Fair pricing models for the Big Data era

Furthermore for students hoping to continue into research, we have seven major research groups: computer vision and graphics; embedded, networked, and distributed systems; formal analysis, theory, and algorithms; human computer interaction; inference, dynamics, and interaction; information retrieval; software engineering and information security. Most MSc students choose projects offered by these groups, giving them an opportunity to go on to PhD study.

Information for international students

For applicants whose first language is not English, the University sets a minimum English Language proficiency level. International English Language Testing System (IELTS) Academic module (not General Training): overall score 6.5; no sub-test less than 6.0. IBTOEFL: 92; no sub-test less than 20

Fees and funding

UK students
£6800
International students
£18200

http://www.gla.ac.uk/postgraduate/taught/datascience/

Qualification and course duration

MSc

full time
12 months
part time
24 months

PGDip

full time
9 months
part time
21 months

Course contact details

Name
Dr Ron Poet
Email
Ron.Poet@glasgow.ac.uk