Postgraduate study

High Performance Computing with Data Science MSc

Awards: MSc

Study modes: Full-time, Part-time

Funding opportunities

You will study at EPCC, the UK’s leading supercomputing centre and a Centre of Excellence within the University's College of Science and Engineering. EPCC is a major provider of high performance computing (HPC) training in Europe with an international reputation for excellence in HPC education and research.

HPC is the use of powerful processors, networks and parallel supercomputers to tackle problems that are very computationally or data-intensive. You will learn leading-edge HPC technologies and skills to exploit the full potential of the world’s largest supercomputers and multicore processors. This is a well-established programme that has been successful in training generations of specialists in parallel programming.

Data science involves the manipulation, processing and analysis of data to extract knowledge, and HPC provides the power that underpins it. You will learn the multidisciplinary skills and knowledge in both HPC and data science to unlock the knowledge contained in the increasingly large, complex and challenging data sets that are now generated across many areas of science and business. Our staff have a wealth of expertise across HPC, parallel programming technologies and data science.

This is an applied and practically-focused programme where you will develop and run software using a range of programming languages and techniques. A core set of courses requires knowledge of one of C, C++, or Fortran; prior knowledge of any of these is not required as students are introduced to them at the start of the programme. Students should already be competent programmers e.g. in Java, Python, or one of the above-noted languages (see entry requirements, below), and keen to learn new programming approaches.

EPCC is the UK’s leading supercomputing centre with staff who are experienced HPC practitioners. EPCC is a major provider of HPC training in Europe with an international reputation for excellence in HPC education and research and a well-established on-campus MSc programme that has been successful in training generations of specialists in parallel programming. Students benefit from access to advanced HPC systems with recent examples including ARCHER (the UK national Tier 1 supercomputing service with over 100,000 cores) and Cirrus, an heterogeneous system EPSRC Tier-2 National HPC Facility.

For an insight into EPCC’s current, including cutting edge, systems please our website.

The MSc programme takes the form of two semesters of taught courses followed by a dissertation project.

Your studies will have a strong practical focus and you will have access to a wide range of HPC platforms and technologies. You will take seven compulsory courses, which provide a broad-based coverage of the fundamentals of HPC, parallel computing and data science. The option courses focus on specialist areas relevant to computational science, data science, and parallel computing. Assessment is by a combination of coursework and examination.

Taught courses

Compulsory courses:

  • Fundamentals of Data Management (Semester 1)
  • Message-Passing Programming (Semester 1)
  • Programming Skills (Semester 1)
  • Threaded Programming (Semester 1)
  • Data Analytics with High Performance Computing (Semester 2)
  • Software Development (Semester 2)
  • Project Preparation (Semester 2)

HPC Optional courses (at least 2 of):

  • Numerical Algorithms for High Performance Computing (Semester 1)
  • Design and Analysis of Parallel Algorithms (Semester 1)
  • HPC Architectures (Semester 1)
  • Advanced Parallel Techniques (Semester 2)
  • Advanced Message-passing Programming (Semester 2)
  • Parallel Design Patterns (Semester 2)
  • Performance Programming (Semester 2)

Data Science Optional Courses (maximum two or three of, depending on credit-amount, access may be subject to enrolment limits, meeting individual course prerequisites set by the School of Informatics and individual courses may not run in an individual year):

  • Machine Learning Practical (Semester 1 & 2)
  • Bioinformatics 1 (Semester 1)
  • Extreme Computing (Semester 1)
  • Image and Vision Computing (Semester 1)
  • Text Technologies for Data Science (Semester 1)
  • Advanced Topics in Foundations of Databases (Semester 2)
  • Bioinformatics 2 (Semester 2)
  • Distributed Systems (Semester 2)
  • Probabilistic Modelling and Reasoning (Semester 2)
  • Reinforcement Learning (Semester 2)
  • One 10 credit SCQF Level 11 course from the College of Science and Engineering

Dissertation

After completing the taught courses, students work on a three-month individual project leading to a dissertation.

Dissertation projects may be either research-based or industry-based with an external organisation, with opportunities for placements in local companies.

Industry-based dissertation projects

Through our strong links with industry, we offer our students the opportunity to undertake their dissertation project with one of a wide range of local, national and even international companies.

An industry-based dissertation project can give you the opportunity to enhance your skills and employability by tackling a real-world project, gaining workplace experience, exploring potential career paths and building relationships with industrial partners.

Find out more about compulsory and optional courses

We link to the latest information available. Please note that this may be for a previous academic year and should be considered indicative.

AwardTitleDurationStudy mode
MScHigh Performance Computing with Data Science1 YearFull-timeProgramme structure 2019/20

Our graduates are employed across a range of commercial areas, for example software development, petroleum engineering, finance and HPC support. Others have gone on to PhD research in fields that use HPC technologies, including astrophysics, biology, chemistry, geosciences, informatics and materials science.

A UK 2:1 honours degree, or its international equivalent, in a relevant subject such as computer science and informatics, physics, mathematics, engineering, biology, chemistry and geosciences.

You must be a competent programmer in at least one of C, C++, Python, Fortran, or Java and should be familiar with mathematical concepts such as algebra, linear algebra and probability and statistics.

We will also consider your application if you don’t have formal programming training (e.g. if you are primarily self-taught), or if you have a 2:2 honours degree with high marks in computational courses and/or additional relevant work experience. Your application should clearly demonstrate your relevant experience.

International qualifications

Check whether your international qualifications meet our general entry requirements:

English language requirements

You must demonstrate a level of English language competency at a level that will enable you to succeed in your studies, regardless of your nationality or country of residence.

English language tests

We accept the following English language qualifications at the grades specified:

  • IELTS Academic: total 6.5 with at least 6.0 in each component

  • TOEFL-iBT: total 92 with at least 20 in each section

  • PTE Academic: total 61 with at least 56 in each of the Communicative Skills scores

  • CAE and CPE: total 176 with at least 169 in each paper

  • Trinity ISE: ISE II with distinctions in all four components

Your English language qualification must be no more than three and a half years old from the start date of the programme you are applying to study, unless you are using IELTS, TOEFL, PTE Academic or Trinity ISE, in which case it must be no more than two years old.

Degrees taught and assessed in English

We also accept an undergraduate or postgraduate degree that has been taught and assessed in English in a majority English speaking country, as defined by UK Visas and Immigration:

We also accept a degree that has been taught and assessed in English from a university on our list of approved universities in non-majority English speaking countries.

If you are not a national of a majority English speaking country, then your degree must be no more than three and a half years old at the beginning of your programme of study.

Find out more about our language requirements:

AwardTitleDurationStudy mode
MScHigh Performance Computing with Data Science1 YearFull-timeTuition fees
MScHigh Performance Computing with Data Science2 YearsPart-timeTuition fees
MScHigh Performance Computing with Data Science3 YearsPart-timeTuition fees

Featured funding

UK government postgraduate loans

If you live in the UK, you may be able to apply for a postgraduate loan from one of the UK’s governments. The type and amount of financial support you are eligible for will depend on your programme, the duration of your studies, and your residency status. (Programmes studied on a part-time intermittent basis are not eligible.)

Other funding opportunities

Search for scholarships and funding opportunities:

  • Postgraduate Programmes Manager, Ben Morse
  • Phone: +44 (0)131 651 3398
  • Contact: msc@epcc.ed.ac.uk
  • Programme Director, Dr David Henty
  • Phone: +44 (0)131 651 3398
  • Contact: msc@epcc.ed.ac.uk
  • EPCC
  • The Bayes Centre
  • 47 Potterrow
  • Central Campus
  • Edinburgh
  • EH8 9BT

Applications for our postgraduate taught programmes can be submitted at any time during the year, and will be evaluated as they are received. We will make a small number of offers to the most outstanding candidates on an ongoing basis, but please do not be concerned if you do not hear initially as offers are regularly made in batches.

If you have any concerns please contact: msc@epcc.ed.ac.uk.

You must submit one reference with your application.

Find out more about the general application process for postgraduate programmes:

Further information

  • Postgraduate Programmes Manager, Ben Morse
  • Phone: +44 (0)131 651 3398
  • Contact: msc@epcc.ed.ac.uk
  • Programme Director, Dr David Henty
  • Phone: +44 (0)131 651 3398
  • Contact: msc@epcc.ed.ac.uk
  • EPCC
  • The Bayes Centre
  • 47 Potterrow
  • Central Campus
  • Edinburgh
  • EH8 9BT