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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2020/2021

Information in the Degree Programme Tables may still be subject to change in response to Covid-19

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DRPS : Course Catalogue : School of Informatics : Informatics

Postgraduate Course: Doing Research in Natural Language Processing (INFR11194)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits20 ECTS Credits10
SummaryThis course introduces critical skills needed to do research in natural language processing: identifying research questions; proposing methods to answer research questions; and communicating results orally and in writing to a scientific audience. The course emphasizes that NLP research draws on computational, mathematical, and linguistic perspectives to research, and exposes students to the key research skills from each of these perspectives.
Course description This course introduces critical skills needed to do research in natural language processing: identifying research questions; proposing methods to answer research questions; and communicating results orally and in writing to a scientific audience. The course emphasizes that NLP research draws on computational, mathematical, and linguistic perspectives to research, and exposes students to the key research skills from each of these perspectives.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Students MUST NOT also be taking Informatics Project Proposal (INFR11147) OR Informatics Research Review (INFR11136)
Other requirements This course is ONLY available to students on the first year of the PhD with Integrated Study in Natural Language Processing.
Course Delivery Information
Academic year 2020/21, Not available to visiting students (SS1) Quota:  None
Course Start Full Year
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 6, Seminar/Tutorial Hours 26, Feedback/Feedforward Hours 3, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 161 )
Additional Information (Learning and Teaching) The course will meet approximately once per week for a full academic year.
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Written Examination: 0%
Practical Examination: 0%
Coursework: 100%

120 hours across 3 assessed assignments, and additional formative assignments evaluated by peer assessment, to include short writing assignments and practice presentations.

Students will be assessed on two written courseworks and on an oral presentation.

1. A research report on a small practical project in natural language processing. The report will require the student to report on the results of a single experiment, proof, or prototype related to a question selected from a set provided by the course organizers (assessing learning outcome 4).

2. An oral presentation on a recent research result in natural language processing (assessing learning outcome 3).

3. A research proposal related to natural language processing. The proposal will require the student to motivate a question based on reading the literature (assessing outcome 1) and propose methods to answer. It (assessing outcome 2). It is expected that the research proposal will be for a substantial research project, for example forming part of the students initial PhD research work.
Feedback 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.

Formative writing assignments will be reviewed by peers under a provided rubric.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Critically read, assess, and synthesize scientific literature in natural language p rocessing and related fields.
  2. Identify new research questions in natural language processing and propose experimental, mathematical, or engineering methods to answer them.
  3. Communicate research results in natural language processing orally to a scient ific audience.
  4. Communicate research results in natural language processing in writing to a scientific audience.
Reading List
The course will draw on readings from:

* Zobel, Writing for Computer Science

* Williams and Colomb. Style: Towards Clarity and Grace

Additional material maybe drawn from similar sources to IRR/ IPP.
Additional Information
Graduate Attributes and Skills Students on the course will develop skills in critically reviewing, consolidating, and extending knowledge; communicating with peers, more senior colleagues, and specialists; and undertaking critical evaluations of a wide range of numerical and graphical data.
Special Arrangements Only available to students on the PhD with integrated study in Natural Language Processing.
KeywordsNa tural language processing,research skills
Contacts
Course organiserDr Frank Keller
Tel: (0131 6)50 4407
Email: Frank.Keller@ed.ac.uk
Course secretaryMs Lindsay Seal
Tel: (0131 6)50 2701
Email: lindsay.seal@ed.ac.uk
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