Postgraduate Course: Individual Project in Advanced Natural Language Processing (80 credits) (INFR11204)
|School||School of Informatics
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Not available to visiting students
|Summary||This course requires students to undertake a significant piece of individual, self-directed research in natural language processing, developed in consultation with a member of staff. The project requires the application of skills learned through other courses and requires the development and synthesis of new skills, including problem-solving and communication skills.
This course requires students to undertake a significant piece of individual, self-directed research in natural language processing, developed in consultation with a member of staff. The project requires the application of skills learned through other courses and requires the development and synthesis of new skills, including:
* The ability to identify new research questions in NLP based on a review of the literature.
* The ability to design and carry out experiments, implement systems, or prove mathematical results needed to answer NLP research questions.
* The ability to communicate novel scientific results orally and in writing.
Course Delivery Information
|Academic year 2022/23, Not available to visiting students (SS1)
|Learning and Teaching activities (Further Info)
Lecture Hours 1,
Seminar/Tutorial Hours 5,
Feedback/Feedforward Hours 2,
Programme Level Learning and Teaching Hours 16,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
800 hours, including formative assignments evaluated by peer assessment at group meetings.
Students will be assessed on the basis of a short written report in the style of a conference paper; and on an oral presentation which may include a demonstration. The report must describe substantial and original research, and will typically include:
* A section motivating why the research is relevant to NLP and identifying the major claims resulting from the research.
* A concise explanation of methods, experimental design, novel implementation details, or mathematical background, as appropriate to the topic.
* Results and analysis, relating these back to the main claims.
* A background section explaining how the research relates to other historical or contemporary research in NLP.
* A section explaining further questions that arise from the research and outlining questions for further research, if appropriate.
||Feedback on assessed coursework will be provided within two weeks, and will include formative comments on work in relation to concepts studied in the course.
Report drafts will be reviewed by peers, the course instructor, the TA, and individual supervisors under a provided rubric.
|No Exam Information
On completion of this course, the student will be able to:
- Identify a specific research question in natural language processing and propose experimental, mathematical, or engineering methods to answer it.
- Carry out and precisely document methods to answer research questions in natural language processing.
- Communicate novel research results in natural language processing to a scientific audience orally and in writing.
|Graduate Attributes and Skills
||Students on the course will develop skills in using a range of specialised skills, techniques, practices and/or materials that are at the forefront of, or informed by forefront developments; In applying a range of standard and specialised research and/or equivalent instruments and techniques of enquiry; planning and executing a significant project of research, investigation or development; demonstrating originality and/or creativity, including in practices; exercise substantial autonomy and initiative in professional and equivalent activities.
||This course is ONLY available to students on the first year of the PhD with Integrated Study in Natural Language Processing.
|Keywords||Natural language processing,research skills
|Course organiser||Dr Hao Tang
|Course secretary||Ms Lindsay Seal
Tel: (0131 6)50 2701