Last modified: 28 Jun 2018 10:27
The aim of the course is to introduce students who have some background in computing to (1) the varied aims for which Natural Language Generation (NLG) is pursued, (2) the main rule based and statistical methods that are used in NLG, and (3) some of the main NLG algorithms and systems. The course will cover NLG both as a theoretical enterprise (e.g., for constructing models of language production) and as practical language engineering, paying particular attention to the link between NLG and data science. Some programming experience is expected.
Study Type | Postgraduate | Level | 5 |
---|---|---|---|
Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
Campus | Old Aberdeen | Sustained Study | No |
Co-ordinators |
|
Information on contact teaching time is available from the course guide.
1st Attempt: 1 two-hour written examination (75%); continuous assessment (25%)
Resit: Candidates only resit those components (written examination, continuous assessment) which the failed at first attempt. Written examination at resit is 1 two-hour paper.
There are no assessments for this course.
We have detected that you are have compatibility mode enabled or are using an old version of Internet Explorer. You either need to switch off compatibility mode for this site or upgrade your browser.