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Advanced Computer Science (Artificial Intelligence) MSc

Advanced Computer Science (Artificial Intelligence) MSc

Key information
DATA SOURCE : IDP Connect

Qualification type

MSc - Master of Science

Subject areas

Computer Science Artificial Intelligence (Ai)

Course type

Taught

Course Summary

Overview

This programme will equip you with specialist knowledge in this exciting field and allow you to explore a range of topics in computer science.

Core modules will give you a foundation in topics like systems programming and algorithms, as well as the basics of machine learning and knowledge representation. You’ll also choose from optional modules focusing on topics like bio-inspired computing or text analytics, or broaden your approach with topics like mobile app development.

You’ll gain a broad perspective on intelligent systems, covering evolutionary models, statistical and symbolic machine learning algorithms, qualitative reasoning, image processing, language understanding and bio-computation as well as essential principles and practices in the design, implementation and usability of intelligent systems.

You’ll benefit from world-class facilities to support your learning, including:

  • a state-of the art cloud computing lab with a 16-node cluster
  • a large High Performance Computing (HPC) resource consisting of several clusters which are used for all forms of predictive modelling, data analysis and simulation
  • a visualisation lab including a Powerwall, benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker
  • Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices
  • Twin Immersion Corp CyberGloves
  • power meters attached to cloud computing servers,
  • rendering cluster and labs containing both Microsoft and Linux platforms, among others

Learning and teaching

Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.

Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.

Assessment

You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.

Career opportunities

Computing is an essential component of nearly every daily activity, from the collection and processing of information in business, through to smart systems embedded in devices, image processing in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web. This programme will give you the practical skills to enter many areas of applied computing, working as application developers, system designers and evaluators. Links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well-prepared for a range of careers, as well as further research at PhD level. Graduates have found success in a wide range of careers working as business analysts, software engineers, web designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.

Different course options

Study mode

Full time

Duration

12 months

Start date

SEP-20

Modules

On completion of this module, students should be able to understand how natural computing and conventional AI can complement each other; understand algorithms that are based on cooperative behaviour of distributed systems with no, or little central control; understand, design and apply simple genetic algorithms; understand the relation between artificial neural networks and statistical learning; understand how the fields of artificial neural networks and computational and cognitive neuroscience inform each other; read and discuss recent research papers in selected journals and conferences and give a presentation on a recent topic in bio-inspired computing.

Tuition fees

UK fees
Course fees for UK / EU students

Please contact university and ask about this fee

Average for all Postgrad courses (per year)

£5,202

International fees
Course fees for non-UK / EU students

Please contact university and ask about this fee

Average for all Postgrad courses (per year)

£12,227

Entry requirements

Students need a bachelor degree with a 2:1 (hons) in computing or a related subject with a substantial computing element. Relevant work experience will also be considered. We expect you to have programming competence, some prior experience of systems development and knowledge of data structures and algorithms. All applicants will need to have GCSE English Language at grade C or above, or an appropriate English language qualification. We accept a range of international equivalent qualifications.