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M.Sc. Computer Science

Course Content

 The MSc programme runs throughout an entire year, with 2 semesters featuring the taught component of the MSc.

On completion of the first 2 semesters, students work full-time on their individual dissertations throughout the summer months, with final dissertations due in before the start of the following academic year.

The following diagram gives an overview off the program, showing the available modules and the time of the year that they run.  Students take a set of core modules, choose from a set that are specific to their strand and can take a number of options from other strands.  All students will complete a substantial dissertation in their chosen area. For detailed information on individual modules and strands, visit the module info page or go directly to the Data Science, Intelligent Systems, Future Networked Systems or Graphics & Vision Technologies strand pages.

General Course Structure

Program Level Learning Outcomes

On successful completion of this programme, students will be able to:

  1.  Critically discuss the complexities of modern computing systems specific to the strand

  2.    Analyse the architectures, design approaches, technologies and standards underpinning state of the art computer systems specific to the strand

  3.  Identify commercial opportunities that arise in the field, and be able to formulate a business plan to develop that opportunity either as an entrepreneur or within a larger organisation

  4. Apply advanced principles of computer and data science and state of the art techniques to the identification, formulation, analysis and solution of real-world problems specific to the strand
     
  5.  Appraise complex information, formulate judgements and clearly communicate knowledge and conclusions related to the strand in written and verbal formats

  6. Pursue with a degree of independence an original research project, including project planning; identification, appraisal and application of appropriate techniques; identification of the limitations of different state of the art techniques and technologies; formulation of logical conclusions; appraisal of the project outcome in the context of related published work; and communication of the findings in an appropriate scholarly manner.