Taught course

Data Science

Institution
University of Glasgow · School of Computing Science
Qualifications
MSc

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, together with experience of conducting a development project, 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 conducting a data science project.

Why Glasgow?

  • The School of Computing Science is consistently highly ranked achieving 2nd in Scotland and 10th in the UK (Complete University Guide 2017)
  • 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.
  • We currently have 15 funded places to offer to home and EU students.
  • You will have opportunities to meet employers who 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
  • Data fundementals
  • Information retrieval
  • Machine learning
  • Research methods and techniques
  • Text as data
  • Web science
  • Masters team project.

Optional courses

  • Advanced networking and communications
  • Advanced operating systems
  • Algorithmics
  • Artificial intelligence
  • Big data: systems, programming and management
  • Computer architecture
  • Computer vision methods and applications
  • Cryptography and secure development
  • Cyber security forensics
  • Cyber security fundamentals
  • Distributed algorithms and systems
  • Enterprise cyber security
  • Functional programming
  • Human computer interaction
  • Human computer interaction: design and evaluation
  • Human-centred security
  • Information retrieval
  • Internet technology
  • IT architecture
  • Machine learning
  • Mobile human computer interaction
  • Modelling reactive systems
  • Safety critical systems.
  • Software project management
  • Theory of Computation

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

If you wish to engage in part-time study, please be aware that dependent upon your optional taught courses, you may still be expected to be on campus on most week days.

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.

Examples projects

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 four major research sections:

  • human computer interaction (GIST)
  • formal analysis, theory and algorithms (FATA)
  • information, data and analysis (IDA)
  • computer systems (GLASS)

Most MSc students choose projects offered by these groups, giving them an opportunity to go on to PhD study. See details of our research

Industry Links and Employability

  • The advent of Big Data tools in recent years has facilitated the large-scale mining of voluminous data, to allow actionable knowledge and understanding, known as Data Science. For instance, search engines can gain insights into how ambiguous a query is according to the querying and clicking patterns of different users. Data Science combines a thorough background in Big Data processing techniques, combined with techniques from information retrieval and machine learning, to permit coherent and principled solutions allowing real insights and predictions to be obtained from data.
  • The programme includes a thorough grounding in professional software development, together with experience of conducting a development project. The programme will prepare you for a responsible position in the IT industry.
  • The School of Computing Science has extensive contacts with industrial partners who contribute to several of their taught courses, through active teaching, curriculum development, and panel discussion. Recent contributors include representatives from IBM, J.P. Morgan, Amazon, Adobe, Red Hat and Bing.
  • During the programme students have an opportunity to develop and practice relevant professional and transferrable skills, and to meet and learn from employers about working in the IT industry.

The Data Lab

We work closely with The Data Lab, an internationally leading research and innovation centre in data science. Established with an £11.3 million grant from the Scottish Funding Council, The Data Lab will enable industry, public sector and world-class university researchers to innovate and develop new data science capabilities in a collaborative environment. Its core mission is to generate significant economic, social and scientific value from data. Our students will benefit from a wide range of learning and networking events that connect leading organisations seeking business analytics skills with students looking for exciting opportunities in this field.

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
  • or equivalent scores in another recognised qualification:

Fees and funding

UK students
£7700
International students
£19500

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

Qualification and course duration

MSc

full time
12 months
part time
24 months

Course contact details

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