Advanced Natural Language Processing (968G5JN)

15 credits, Level 7 (Masters)

Spring teaching

This module builds on the foundations provided by the Applied Natural Language Processing module.

You’ll develop your knowledge and understanding of key topics including:

• word sense disambiguation

• vector space models of semantics

• named entity recognition

• topic modelling

• machine translation

You’ll take part in in‑depth discussion of research papers related to the key topics. You’ll also examine 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 help you improve your Python programming skills. You’ll also experiment with off‑the‑shelf technology and develop your research skills.

Contact hours and workload

This module is approximately 150 hours of work. This breaks down into about 42 hours of contact time and about 108 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 2026/27. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum.

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

Courses

This module is offered on the following courses:

• Mathematics with Data Science MMath
• Physics with Data Science MPhys