Natural Language Engineering (G5119)
15 credits, Level 5
In this module, you are introduced to techniques and concepts involved in the analysing of text by machine - with particular emphases on various practical applications that this technology drives.
You study core, generic text processing models, such as:
- part-of-speech tagging
- named entity recognition
- phrasal chunking
- dependency parsing.
You also cover related problems and application areas, such as:
- document classification
- information retrieval
- information extraction.
As part of this, you make extensive use of the Natural Language Toolkit, which is a collection of natural language processing tools written in the Python programming language.
50%: Practical (Laboratory)
30%: Coursework (Report)
70%: Examination (Computer-based examination)
Contact hours and workload
This module is approximately 150 hours of work. This breaks down into about 44 hours of contact time and about 106 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.
We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2022/23. However, there may be changes to these modules in response to COVID-19, staff availability, student demand or updates to our curriculum. We’ll make sure to let our applicants know of material changes to modules at the earliest opportunity.
This module is offered on the following courses: