MSc Advanced Computing - Machine Learning, Data Mining and High-Performance ComputingFind a programme
|Faculty||Faculty of Engineering|
|Programme length||One year full-time|
|Location of programme||Clifton campus|
|Part-time study available||No, full-time only|
|Open to international students||Yes|
|Start date||September 2017|
Machine learning, data mining and high-performance computing are concerned with the automated analysis of large-scale data by computer, in order to extract the useful knowledge hidden in it. Using state-of-the-art artificial intelligence methods, this technology builds computer systems capable of learning from past experience, allowing them to adapt to new tasks, predict future developments, and provide intelligent decision support. Bristol's recent investment in the BlueCrystal supercomputer - and our Exabyte Informatics research theme - show our commitment to research at the cutting edge in this area.
This programme is aimed at giving you a solid grounding in machine learning, data mining and high-performance computing technology, and will equip you with the skills necessary to construct and apply these tools and techniques to the solution of complex scientific and business problems.
Fees for 2017/18
Fees quoted are per annum and subject to annual increase.
University of Bristol students and graduates can benefit from a ten per cent reduction in tuition fees for postgraduate study. Check your eligibility for an alumni scholarship.
Funding for 2017/18
Further information on funding for prospective UK, EU and international postgraduate students.
Your course will cover the following core subjects:
- Introduction to Machine Learning
- Research Skills
- Statistical Pattern Recognition
- Uncertainty Modelling for Intelligent Systems
Depending on previous experience or preference, you are then able to take optional units which typically include:
- Artificial Intelligence with Logic Programming
- Bio-inspired Artificial Intelligence
- Cloud Computing
- Computational Bioinformatics
- Computational Genomics and Bioinformatics Algorithms
- Computational Neuroscience
- High Performance Computing
- Image Processing and Computer Vision
- Robotics Systems
- Server Software
- Web Technologies
You must then complete a project that involves researching, planning and implementing a major piece of work. The project must contain a significant scientific or technical component and will usually involve a software development component. It is usually submitted in September.
This programme is updated on an ongoing basis to keep it at the forefront of the discipline. Please refer to the University's programme catalogue for the latest information on the most up-to-date programme structure.
Find out more about the programme structure and units available for MSc Advanced Computing - Machine Learning, Data Mining and High-Performance Computing
An upper second-class honours degree (or equivalent) in computer science or related discipline. Good knowledge of programming is essential.
See international equivalent qualifications on the International Office website.
|Application method||Online application form|
|English language requirements||
Further information about English language requirements
|Admissions statement||Read the programme admissions statement for important information on entry requirements, the application process and supporting documents required.|
Skilled professionals and researchers who are able to apply these technologies to current problems are in high demand in today's job market.
Due to the high volume of applications received, this programme is now closed to applicants from the UK and EU.
In the interests of selecting a balanced international student cohort, the Faculty of Engineering will continue to welcome applications from international students that fulfil our admissions criteria. The application deadline for international students is 18 August 2017. Early application recommended; places may fill before our deadline.
Find out more about becoming a student at Bristol, and the support we offer to international students.
REF 2014 results
- 31% of research is world-leading (4 star)
- 56% of research is internationally excellent (3 star)
- 12% of research is recognised internationally (2 star)
- 1% of research is recognised nationally (1 star)
Results are from the most recent UK-wide assessment of research quality, conducted by HEFCE. More about REF 2014 results.
Get in touch
For questions regarding study and admission contact our Enquiries Team Phone: +44 (0) 117 394 1649 Email: firstname.lastname@example.org