Applied Natural Language Processing (955G5)

15 credits, Level 7 (Masters)

Autumn teaching

Applied Natural Language Processing concerns the theory and practice of automatic text processing technologies.

In this module, you study core, generic text processing models, such as:

  • tokenisation
  • segmentation
  • stemming
  • lemmatisation
  • 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.

You gain hands-on experience with the practical aspects of this module through weekly laboratory sessions.

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.

Teaching

50%: Lecture
41%: Practical (Laboratory)
9%: Seminar (Class)

Assessment

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.

This module is running in the academic year 2021/22. We also plan to offer it in future academic years. However, we are constantly looking to improve and enhance our courses. There may be changes to modules in response to student demand or feedback, changes to staff expertise or updates to our curriculum. We may also need to make changes in response to COVID-19. We’ll make sure to let our applicants know of material changes to modules at the earliest opportunity.