Course Details in 2026/27 Session

Module Title	LM Natural Language Processing (Extended)
School	Computer Science
Department	Computer Science
Module Code	06 37812
Module Lead	Dr Mark Lee
Level	Masters Level
Credits	20
Semester	Semester 2
Pre-requisites	LH Neural Computation - (06 32167) LM Neural Computation (Extended) - (06 32212)
Co-requisites
Restrictions	None
Contact Hours	Lecture-33 hours Guided independent study-167 hours Total: 200 hours
Exclusions
Description	Natural Language Processing enables computers to understand and reason about human languages such as English and has resulted in many exciting technologies such as conversational assistants, machine translation and (intelligent) internet search. This module would provide the theoretical foundations of NLP as well as applied techniques for extracting and reasoning about information from text. The module explores three major themes: Computational Models of human cognition such as memory, attention and psycholinguisticsSymbolic AI methods for processing language such as automated reasoning, planning, parsing of grammar, and conversational systems. Statistical Models of Language including the use of machine learning to infer structure and meaning.
Learning Outcomes	By the end of the module students should be able to: Demonstrate an understanding of the major topics in Natural Language Processing Understand the role of machine learning techniques in widening the coverage of NLP systems Demonstrate an ability to apply knowledge-based and statistical techniques to real-world NLP problems Demonstrate the capacity to independently study, understand, and critically evaluate advanced materials or research articles in the subject areas covered by this module
Assessment	37812-01 : Examination : Exam (Centrally Timetabled) - Written Unseen (80%) 37812-02 : Continuous Assessment : Coursework (20%)
Assessment Methods & Exceptions	Assessment: 2 hr Examination (80%) ,Continuous Assessment (20%) Reassessment: 2 hr Examination (100%)
Other
Reading List