MRes Natural Computation - 2017
|Programme Title||Natural Computation|
|School/Department||School of Computer Science|
|Length of Programme||1 years|
|Awarding Institution||The University of Birmingham|
|QAA Benchmarking Groups||Computing|
Educational Aims Of Programme
- Meet the increasing need from industry for graduates equipped with a knowledge of natural computation techniques.
- Provide a solid foundation in natural computation for graduates to pursue a research and development career in industry or to pursue further studies (e.g. PhD).
- Give up-to-date coverage of current topics in natural computation (such as evolutionary algorithms, co-evolution, evolutionary design, nature-inspired optimisation techniques, evolutionary games, novel learning algorithms, artificial neural networks, the theory of natural computation).
Programme Outcomes and Learning, Teaching and Assessment Strategies
Knowledge and Understanding
- The ideas and concepts underlying a variety of natural computation techniques.
- The strength and weakness of natural computation techniques and the similarities and differences between these techniques and other existing techniques.
- Applications of these techniques to solve large and complex problems in industry.
Skills & Other Attributes
- Given a real-world problem, identify whether natural computation techniques are likely to provide a good solution and then select appropriate techniques from those available.
- Derive efficient solutions to appropriate non-trivial problems using natural computation techniques alone or in combination with other techniques and implement these solutions using both 'off the shelf' software and software they themselves write.
- By the end of the programme, carry out original research and development (e.g. in industry or for a subsequent PhD) with limited supervision, both in the field of natural computation and in allied fields
- Use appropriate methods for literature searching and information retrieval
- Know and apply a variety of research methods, including experimental design and the analysis of data
- Please note: The modules listed on the website for this programme are regularly reviewed to ensure they are up-to-date and informed by the latest research and teaching methods. Unless indicated otherwise, the modules listed for this programme are for students starting in 2017. We aim to publish any changes to compulsory modules and programme structure for 2018 entry by 1 September 2017 and recommend you refer back to this page shortly after that date for any changes. On rare occasions, we may need to make unexpected changes to compulsory modules after that date; in this event we will contact offer holders as soon as possible to inform or consult them as appropriate.