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Featured byThe University of Edinburgh
Overview
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 High Performance Computing with Data Science programme offered by The University of Edinburgh 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.
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.Programme Structure
Courses include:
- Fundamentals of Data Management
- Message-Passing Programming
- Programming Skills
- Threaded Programming
- Data Analytics with High Performance Computing
- Software Development
- Project Preparation
Key information
Duration
- Full-time
- 12 months
- Part-time
- 24 months
- Flexible
Start dates & application deadlines
- Starting
- Apply before
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More details
Language
English
IELTS 6.5
TOEFL® IBT 92
Credits
180 alternative credits
Delivered
On Campus
Disciplines
Computer Sciences Data Science & Big Data View 734 other Masters in Computer Sciences in United KingdomAcademic requirements
GPA Upper Second Class
English requirements
IELTS 6.5
TOEFL® IBT 92
Other requirements
General requirements
- 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.
Tuition Fee
To alway see correct tuition fees
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International
31100 GBP/yearTuition FeeBased on the tuition of 31100 GBP per year during 12 months. -
National
14400 GBP/yearTuition FeeBased on the tuition of 14400 GBP per year during 12 months.
Part-time fees per year MSc (2 years)
- Home - £7,200
- International/EU - £15,550
Part-time fees per year MSc (3 years)
- Home - £4,800
- International/EU - £10,370
Living costs for Edinburgh
725 - 1167 GBP /month
Living costs
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
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