production
Skip to Content

Log In

  1. University Home
  2. Catalogue of Courses
  3. Undergraduate
  4. 2024-2025
  5. SCNU Joint Institute Computing Science
  6. JC4003: Natural Language Processing

JC4003: NATURAL LANGUAGE PROCESSING (2024-2025)

Last modified: 14 Aug 2024 17:16


Course Overview

Natural Language Processing (NLP) is an influential topic that relates to Artificial Intelligence, Linguistics and Human Computer Interaction. NLP engineers are in high demand at companies such as Google, Facebook, Twitter, Yahoo and Microsoft that require sophisticated analysis of text on the internet. This course covers a range of theoretical and applied topics related to how computers interpret human language, and also how computers can generate human language; for example, to summarise data. Topics include grammar formalisms and algorithms for parsing sentences, natural language semantics, text analytics using sentiment analysis, machine translation, grammar checking and natural language generation from data.

Course Details

Study Type Undergraduate Level 4
Term First Term Credit Points 15 credits (7.5 ECTS credits)
Campus Offshore Sustained Study No
Co-ordinators
  • Dr Tryphon Lambrou

What courses & programmes must have been taken before this course?

  • Any Undergraduate Programme (Studied)
  • Programme Level 4
  • One of BSc In Computing Science (SCNU) or Bsc In Artificial Intelligence (Scnu) or Bsc In Business Management & Information Systems (Scnu)

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

This course will introduce students to the following concepts:

  • Formal linguistic models of English: word categories, sentence constituents, phrase-structure grammar rules, features. Modelling syntactic phenomena.
  • Parsing: shift-reduce parsers, chart parsers, handling ambiguity, definite clause grammars.
  • Semantics and pragmatics: meaning representations, reference, speech acts.
  • Generation: Content determination, sentence planning, and realisation.
  • Applications: grammar checking, machine translation, database interfaces, report generation, dictation.
  • Speech: Hidden Markov Models, statistical language models, speech synthesis.

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers


Details, including assessments, may be subject to change until 30 August 2024 for 1st term courses and 20 December 2024 for 2nd term courses.

Summative Assessments

Computer Programming Exercise

Assessment Type Summative Weighting 25
Assessment Weeks Feedback Weeks

Look up Week Numbers

Feedback

Computer programming exercise including a 1,500-word report
Learning Outcomes
Knowledge LevelThinking SkillOutcome
ProceduralApplyApply knowledge and understanding of natural language semantics, text analytics using sentiment analysis, machine translation, and grammar checking
ProceduralUnderstandDemonstrate knowledge & understanding of a range of theoretical and applied topics related to how computers interpret human language, including grammar formalisms and algorithms for parsing sentences

Exam

Assessment Type Summative Weighting 75
Assessment Weeks Feedback Weeks

Look up Week Numbers

Feedback
Learning Outcomes
Knowledge LevelThinking SkillOutcome
ProceduralApplyApply knowledge and understanding of natural language semantics, text analytics using sentiment analysis, machine translation, and grammar checking
ProceduralEvaluateEvaluate different models of how computers can generate human language
ProceduralUnderstandDemonstrate knowledge & understanding of a range of theoretical and applied topics related to how computers interpret human language, including grammar formalisms and algorithms for parsing sentences

Formative Assessment

There are no assessments for this course.

Resit Assessments

Resubmission of failed elements (pass marks carried forward)

Assessment Type Summative Weighting
Assessment Weeks Feedback Weeks

Look up Week Numbers

Feedback
Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
ProceduralUnderstandDemonstrate knowledge & understanding of a range of theoretical and applied topics related to how computers interpret human language, including grammar formalisms and algorithms for parsing sentences
ProceduralApplyApply knowledge and understanding of natural language semantics, text analytics using sentiment analysis, machine translation, and grammar checking
ProceduralEvaluateEvaluate different models of how computers can generate human language
 

Compatibility Mode

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.