University home > Unit and programme catalogues in 2022/23 > Programme catalogue > Faculty of Engineering > Department of Computer Science > Interactive Artificial Intelligence (PhD) > Specification
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Programme code | 4COSC004R |
---|---|
Programme type | Postgraduate Research Degree |
Programme director(s) |
Peter Flach
|
Faculty | Faculty of Engineering |
School/department | Department of Computer Science |
Teaching institution | University of Bristol |
Awarding institution | University of Bristol |
Mode of study | Full Time |
Programme length | 1 years (full time) |
This section sets out why studying this programme is important, both in terms of inspiring you as an individual and in considering the challenges we face. It describes how this degree programme contributes to:
After having completed their training, students will have acquired and demonstrated the ability to design and implement state-of-the-art end-to-end systems involving significant and purposeful interaction between human and artificial intelligence to provide data-driven and knowledge- intensive solutions to important practical problems.
The learning outcome statements shown below for your programme have been developed with reference to relevant national subject benchmarks (where they exist), national qualification descriptors (see the Framework for Higher Education Qualifications) and professional body requirements.
Teaching, learning and assessment strategies are listed to show how you will be able to achieve and demonstrate the learning outcomes.
This programme provides opportunities for you to develop and demonstrate knowledge and understanding, qualities, skills and other attributes in the following areas:
Programme Intended Learning Outcomes | Learning/teaching methods and strategies |
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|
Lectures, supervised and unsupervised labs, problem classes, group projects, seminars, individual research projects, self study |
Methods of assessment (formative and summative) | |
Written exams, coursework, essays and reports, presentations |
Programme Intended Learning Outcomes | Learning/teaching methods and strategies |
---|---|
|
Lectures, supervised and unsupervised labs, problem classes, group projects, seminars, individual research projects, self study |
Methods of assessment (formative and summative) | |
Written exams, coursework, essays and reports, presentations |
This section describes what is expected from you at each level of your programme. This illustrates increasing intellectual standards as you progress through the programme. These levels are mapped against the national level descriptors published by the Quality Assurance Agency.
Level M/7 - Postgraduate Certificate |
To be eligible for the award of a Postgraduate Certificate students must successfully complete 60 credits of taught units which develop foundational understanding of the topics covered. |
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Level M/7 - Postgraduate Diploma |
To be eligible for the award of a Diploma students must successfully complete 120 credits of taught units. Further units provide opportunities for students to deepen their understanding and develop intellectual skills. By the end of this stage students are expected to have developed considerable individual self-sufficiency and autonomy in learning. |
Level M/7 - Postgraduate Masters |
To be eligible for a MRes award 180 credits from the taught modules plus the dissertation must be successfully completed. Note that the MRes degree will only be awarded to students electing to exit the CDT programme early, before completion of their PhD. At this stage students will be able to perform their own research at an internationally publishable standard. They will also be able to document and communicate their findings to peers and expert practitioners in the field. Their individual capabilities will be enhanced by teamwork and system integration skills. |
For information on the admissions requirements for this programme please see details in the postgraduate prospectus at http://www.bristol.ac.uk/prospectus/postgraduate/ or contact the relevant academic department.
https://www.bristol.ac.uk/engineering/school-sceem/
The maximum period of study for full-time students is 4 years. This catalogue only shows the taught units on the programme and may not show all years of study.
Unit Name | Unit Code | Credit Points | Status | |
---|---|---|---|---|
Computational Logic for Artificial Intelligence | COMSM0022 | 10 | Mandatory | TB-2 |
Dialogue and Narrative | COMSM0023 | 10 | Mandatory | TB-1 |
Machine Learning Paradigms | COMSM0025 | 10 | Mandatory | TB-1 |
Responsible AI | COMSM0027 | 10 | Mandatory | TB-2 |
Applied Data Science (Teaching Unit) | COMS30050 | 0 | Mandatory | TB-2 |
Applied Data Science (Interactive Artificial Intelligence CDT) | COMSM0056 | 10 | Mandatory | TB-2 |
Uncertainty Modelling for Intelligent Systems (CDT) | EMATM0060 | 10 | Mandatory | TB-1 |
Interactive AI Team Project | COMSM0087 | 40 | Mandatory | TB-4 |
Summer Project | COMSM0024 | 60 | Mandatory | TB-4 |
Research Methods in Interactive Artificial Intelligence | COMSM0133 | 20 | Mandatory | TB-4 |
Interactive Artificial Intelligence (MRes) | 180 |
The assessment of the taught component of a doctoral degree is governed by the Regulations and Code of Practice for Taught Programmes and is assessed separately from the research project. Progression to the research project may be dependent on the successful completion of the taught component - please refer to the relevant handbook for the structure of the particular programme.
The pass mark set by the University for any level 7(M) unit is 50 out of 100.
It may be possible to exit the programme with a taught award. For detailed rules on progression please see the Regulations and Code of Practice for Research Programmes and the relevant faculty handbook.
Please note: This specification provides a concise summary of the main features of the programme and the learning outcomes that a typical student might reasonably be expected to achieve and demonstrate if he/she takes full advantage of the learning opportunities that are provided.
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