Electronic Information Engineering (m.sc. / P.grad.dip.) in Trinity College Dublin, Ireland

Electronic Information Engineering (m.sc. / P.grad.dip.) in Trinity College Dublin

This is a one year full time or two year part-time postgraduate course designed to provide graduate engineers with specialist understanding of modern computational products and systems. There is no aspect of modern life that is not now altered by information processing engines. Examples include digital assistants (speech recognition and synthesis), automotive (remote sensing and electronic control systems), the economy (quantitative automated trading), entertainment (audiovideo streaming and cinema visual effects), health (medical imaging), science (computational biology/geography/chemistry/photography) and the digital humanities. The principles enabling the design of this new wave of products are embodied in the discipline of Information Engineering. This course allows graduates to specialise in fundamental theory and applications relating to the generation, distribution, analysis and use of information in engineering and science.

Course Organisation

This M.Sc. course can be taken as either a full-time one year or part-time two year postgraduate course and consists of taught modules and a project amounting to 90 credits. The taught component comprises modules totalling 50 credits. In the first semester, students pursuing the course must take modules worth at least 25 credits, and in the second semester they take the balance of the credits. M.Sc. candidates will, in addition, complete a substantial research project and submit a dissertation which accounts for a further 40 credits to be eligible for consideration for the award of the degree. Part time students are required to take 50 credits of taught modules in the first year and the research project in the second year.

Course Content

All candidates are required to take the following module(s):

                   Research Project/Dissertation (40 credits)

                   Research Methods (15 credits)

                   Statistical Signal Processing (5 credits)

                   Introduction to Deep Learning (10 credits)

 In addition, candidates select a further 20 credits from the following list to bring their total credits to 90:

                   Speech and Audio Engineering (5 credits)

                   Spatial Audio (5 credits)

                   Audio Production Engineering (5 credits)

                   Digital Media Systems (10 credits)

                   Wireless Networks and Communications (5 credits)

                   Complex Systems Science (5 credits)

                   Reconfigurable Hardware for Computational Engineering (10 credits)

Some of the module options in either semester may be withdrawn from time to time and some new modules may be added, subject to demand.