Advanced Natural Language Engineering (G5114)

15 credits, Level 6

Spring teaching

Advanced Natural Language Engineering builds on the foundations provided by the Natural Language Engineering module. You will develop your knowledge and understanding of key topics including word sense disambiguation, vector space models of semantics, named entity recognition, topic modelling and machine translation. 

Seminars will provide an opportunity to discuss research papers related to the key topics and also general issues that arise when developing natural language processing tools, including:

  • hypothesis testing
  • data smoothing techniques
  • domain adaptation
  • generative versus discriminative learning
  • semi-supervised learning 

Labs will provide the opportunity for you to improve your python programming skills, experiment with some off-the-shelf technology and develop research skills.

Teaching

50%: Practical (Laboratory)
50%: Seminar

Assessment

100%: Coursework (Report, Test)

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 5X社区视频 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鈥檙e planning to run these modules in the academic year 2024/25. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum.

We鈥檒l make sure to let you know of any material changes to modules at the earliest opportunity.