M.Sc. Advanced Computing - Machine Learning and Data Mining

  • On Campus
  • 12 months
  • GBP18600 per Year (International

    Tuition fee for the international students.

    )
    GBP8100 per Year (EEA

    European Economic Area tuition fee is applicable to the students from EU countries, Iceland, Liechtenstein, Norway and Switzerland.

    )
  • English ( Take IELTS test or Find a course )
University of Bristol | Bristol, United Kingdom
The Advanced Computing - Machine Learning and Data Mining programme from University of Bristol 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 ML, DM and HPC tools and techniques to the solution of complex scientific and business problems.

Description

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The Advanced Computing - Machine Learning and Data Mining programme from University of Bristol is 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 University 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 ML, DM and HPC tools and techniques to the solution of complex scientific and business problems.

Detailed Course Facts

Start dates and application deadlines

Starting in

  • ( General

    General deadline, applies to everyone.

    )
Tuition fee
  • GBP 18600 per year (International

    Tuition fee for the international students.

    )
  • GBP 8100 per year (EEA

    European Economic Area tuition fee is applicable to the students from EU countries, Iceland, Liechtenstein, Norway and Switzerland.

    )
Duration full-time 12 months
Delivery mode On Campus
Educational variant Full-time

Course Content

In the introductory week you will take a programming proficiency test and will be placed in either an 'experienced' stream or a 'foundation' stream.

This programme is updated on an ongoing basis to keep it at the forefront of the discipline. Please refer to the School website for the latest information on the most up to date programme structure.

You will take the following core units:
  • 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 include:

  • Artificial Intelligence and Computer Vision
  • Cloud Computing
  • Computational Bioinformatics
  • Computational Geonomics 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.

English Language Requirements

IELTS Take IELTS test
6.5
CAE score
180(Grade C)
TOEFL iBT® test (read more)
90

IMPORTANT NOTE: The UK government confirmed new requirements for secure English language testing for visa and immigration purposes. Learn more

Requirements

  • An upper second-class honours degree (or equivalent) in Computer Science or related discipline. Applicants with a mathematics or statistics background may also be considered. Reasonable knowledge of programming is a prerequisite.

Work Experience

No work experience is required.

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