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  • Study Type

    Full time & Part time available

  • Subject Areas

    Computer Science

  • Start Date

    September

  • Course Duration

    1 year full time, 2-3 years part time

  • Course Type

    MSc

  • Course Fees

    Tuition fees vary between degree programmes. Find the specific fees for your chosen programme on our website.

  • Last Updated

    26 November 2018

Course content

Programme Description

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

Our staff have a wealth of expertise across all areas of HPC, parallel programming technologies and data science.

This MSc programme has a strong practical focus and provide access to leading- edge HPC systems such as ARCHER, which is the UK’s largest, fastest and most powerful supercomputer, with more than 100,000 CPU cores.

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.

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Programme structure

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 meeting individual course prerequisites):

*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 SCQF Level 11 course from any part of 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.

Career opportunities

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.


Visit the High Performance Computing with Data Science (MSc) page on the University of Edinburgh website for more details!

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