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BEng Computer Systems Engineering with Industrial Experience / Course details

Year of entry: 2021

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Course unit details:
Natural Language Processing

Unit code COMP34711
Credit rating 10
Unit level Level 3
Teaching period(s) Semester 1
Offered by Department of Computer Science
Available as a free choice unit? No


The course unit will cover key linguistic and algorithmic foundations of natural language processing. It will explore the key challenges in representing, searching and retrieving written documents and processing speech. The course unit will consider both rule-based and machine/deep learning methods, and introduce key applications such as information retrieval, text classification, word sense disambiguation, speech synthesis and speech recognition.


Enabling computers to process data in 'natural language' (the kind of language that people use to communicate with one another) is becoming more and more important. It allows both people to communicate with computers, and the computers to access the enormous amount of material that is stored as natural language text on the web or in document repositories. This course unit provides an introduction to the area of natural language processing (NLP) as one of the key areas of artificial intelligence. It aims to introduce essential components and key applications of NLP, and explain the major challenges in processing large-scale, real-world natural language both in its written and spoken forms.

Teaching and learning methods

Weekly workshops/lectures with structured input and exploratory activities. These will be organised as a blend of brief presentations, hands-on individual and group activities and discussions of materials and tasks that are available online (question-answer sessions).


Weekly laboratories will be individual and group hands-on sessions for trying out new systems or techniques (with set tasks, known answers) and will be also used for preparation for course work. These will be used as surgeries to provide feedback on coursework and as an opportunity to ask questions about the set tasks with more open ended/specific discussions and feedback.


Coursework will provide design, implement and analysis tasks with real-world data.

Assessment methods

Method Weight
Written exam 50%
Written assignment (inc essay) 50%

Study hours

Scheduled activity hours
Lectures 20
Practical classes & workshops 10
Independent study hours
Independent study 70

Teaching staff

Staff member Role
Tingting Mu Unit coordinator

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