Courses

The degree programme is designed to be maximally flexible whilst including some compulsory courses. A path through the programme is given in the table below -- note that this is an example only; other paths are possible.

year 1 Doing research in NLP [20 pts] Foundational courses [40 pts] Group project [20 pts] Individual project [40 pts] PhD research [40 pts]
year 2 Specialist courses [20 pts] Responsible innovation [20 pts] PhD research [140 pts]
year 3 Specialist courses [20 pts] PhD research [160 pts]
year 4 PhD research [180 pts]

Year 1

Students will be routed into courses following a Training Needs Analysis on entry. For example, students with strong computer science or maths background will take more linguistics courses, while students with strong linguistics or cognitive background will take more programming and machine learning courses. There are foundational courses and specialist courses; these are listed in the Degree Programme Table. In year 1, the emphasis is on foundational courses (though specialist courses can also be taken).

The following courses are obligatory for all first year students:

Group Project in Advanced NLP: Students will form interdisciplinary teams to tackle a directed research problem assigned by a team of CDT supervisors. In your group project, you can directly apply the skills you learn in your foundational courses and in the Doing Research in NLP course (see below). As all CDT students in a given year take part, the group project will build the cohort and will also train you in project management and team work skills. The project topics will be defined in consultation with our industrial partners, who may also contribute resources.

Individual Project in Advanced NLP: In addition to the group project, each student will also select a supervisor and define a short individual research project, which may be stand-alone or serve as the basis for a subsequent PhD project. We expect you to work with different supervisors on your individual and group projects, to experience different working styles and broaden your methodological skillset. Some of the individual projects will be conducted with our industrial partners.

Doing Research in NLP: Designed to complement the first-year projects, this course will align with project milestones and teach skills that you can immediately put into practice. In addition to technical skills in NLP at the level required for PhD work, it will teach presentation, communication, and writing skills. Project and time management, as well as NLP specific aspects of responsible innovation, will also be covered.

Years 2-4

In these years, students take a decreasing number of courses, and focus more on their PhD research. Year 2 includes the course Controversies in the Data Society that all students take. In addition, they are expected to take specialist courses that complement their PhD research (see again the Degree Programme Table). There are no obligatory courses in year 3, but students can take more specialist courses if they haven't taken all their required credits yet. Students normally focus fully on PhD research in year 4.

Responsible Research & Innovation

Throughout the four year programme, the CDT includes a strong focus on Responsible Research and Innovation (RRI) considerations.

This includes a compulsory course in semester 2: Controversies in the Data Society and is supported by additional resources such as expert seminar speakers, workshops, industry collaboration, etc.

RRI seeks to promote creativity and opportunities for science and innovation that are socially desirable and undertaken in the public interest. The aim of RRI is to strengthen research and innovation projects, making them more open, transparent, diverse, inclusive and adaptive to changes.

As a recipient of public funding for research, we have a responsibility to ensure that our research is aligned with the principles of RRI, creating value for society in an ethical and responsible way.

Cohort Collaboration

In addition to your research and academic deliverables, you will be required to take full advantage of the cohort and collaborative nature of the broader CDT NLP programme, including:

* outreach and public engagement
* industry/public sector liaison
* event participation and co-ordination
* development of your 'soft skills set'.

Skills Development Training

You will have access to the training courses that the University's Institute for Academic Development runs for PhD students. Topics include Research Planning and Management, Communication and Impact, Personal Effectiveness, Public Engagement, etc.