During the first year of this programme, students must complete 30 credits of compulsory courses and between 35 and 45 credits of elective taught courses.
Students with no previous experience of AI algorithms or Machine Learning must take one of the following options:
Applied Machine Learning (10 credits) (Semester 1, INFR11211) OR
Data Analysis and Machine Learning 4 (ELEE10031) (Semester 2)
Additional courses for future years are under development.
Progression from one year of the programme to the next is conditional on students achieving an average of at least 50% for taught courses, and satisfactory progress of the research project demonstrated during an annual review process.
In order to graduate with the PhD with integrated studies, you must achieve 180 credits of taught components with a pass mark of 50%, of which a minimum of 150 are at SCQF Level 11. The University allows compensation for up to 40 credits of these taught components not passed at this level over the entire programme as defined in the Postgraduate Taught Regulations (see Regulation 56). Yearly progression is also conditional on a candidate being able to meet this criterion.
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