THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2025/2026

Timetable information in the Course Catalogue may be subject to change.

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Jump to: Year 1, Year 2

Year 1 Academic year: 2025/26, Starting in: September

Notes:
During this programme students must complete 80 credits worth of elective courses. Flexibility is given to allow course options to be taken from both Heriot-Watt University and the University of Edinburgh (leading to the +/- 5 credits of variation on selected courses). Before selecting your courses, please ensure you have consulted the Programme Director and Supervisor.

- Within the first 2 years of this programme, students must complete 40 credits of compulsory courses and between 80 and 85 credits of elective taught courses

- Within the first 4 years of the programme students must complete all taught elements, including an additional 60 credits of compulsory courses. In other words, students must have completed 180 credits of taught courses within 4 years.

Note that:
1. The students will be encouraged to take the course ¿Software Testing¿ unless their previous experience indicates they do not have the recommended prerequisites, in which case they choose between Programming Skills (EPCC11017) or Software Development (EPCC11018).

2. Students with no previous experience of AI algorithms or Machine Learning must take one of the following options:
- Applied Machine Learning (20 credits) (Semester 1, INFR11211) this will only be available to CDT students whose lead supervisor is in the School of Informatics, University of Edinburgh
- Machine Learning and Data Analysis 4 (10 credits) (Semester 2, ELEE10033) (available to all SPADS students)

This is to prepare students with no previous AI experience for the second-year course on Case Studies in AI Ethics (10 credits) (Semester 2, INFR11206).


Progression from one year of the programme to the next is conditional on students achieving an average of at least 50% for taught courses taken across the current and previous years of the programme, and satisfactory progress of the research project demonstrated during an annual review process.

In order to graduate with the EngD, 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.

Compulsory courses

You must take these courses

Course options

Compulsory Courses

Select exactly 10 credits of the following courses
AND

Compulsory Courses

Select between 0 and 40 credits of the following courses
AND

AI Hardware Design

Select between 0 and 40 credits of the following courses
AND

Professional Development

Select between 0 and 20 credits of the following courses
AND

Signal Processing, Machine Learning and AI

Select between 0 and 40 credits of the following courses
AND

Systems Engineering and Interfaces

Select between 0 and 40 credits of the following courses
AND

Data Science

Select between 0 and 40 credits of the following courses
AND

HWU Courses

Select between 0 and 40 credits of the following courses

Compulsory Courses

Select exactly 10 credits of the following courses

Year 2 Academic year: 2025/26, Starting in: September

Notes:
During the second year of the programme, students must complete 20 credits of compulsory courses and between 25 and 45 credits of elective taught courses.

Additional courses for future years are under development.

Compulsory courses

You must take these courses

Course options

Compulsory Courses

Select exactly 10 credits of the following courses
AND

Compulsory Courses

Select between 0 and 40 credits of the following courses
AND

AI Hardware Design

Select between 0 and 40 credits of the following courses
AND

Professional Development

Select between 0 and 20 credits of the following courses
AND

Signal Processing, Machine Learning and AI

Select between 0 and 40 credits of the following courses
AND

Systems Engineering and Interfaces

Select between 0 and 40 credits of the following courses
AND

Data Science

Select between 0 and 40 credits of the following courses
AND

HWU Courses

Select between 0 and 40 credits of the following courses

HWU Courses

Select between 0 and 45 credits of the following courses

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