Applied Natural Language Processing UG

Undergraduate | 2026

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Area/Catalogue
COMP 1028
Course ID icon
Course ID
205761
Level of study
Level of study
Undergraduate
Unit value icon
Unit value
6
Course level icon
Course level
1
Study abroad and student exchange icon
Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
No
University-wide elective icon
University-wide elective course
No
Single course enrollment
Single course enrolment
No
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Note:
Course data is interim and subject to change

Course overview

This course examines machine learning techniques that obtain leading results on the problem of natural language processing (NLP). NLP is a critical step towards effective communication between people and machines. You will learn how to represent words and text, the use of deep recurrent models for text prediction, and issues that separate NLP from other application domains. This will be reinforced by applying deep learning tools to NLP through examples and practical projects

Course learning outcomes

  • Understand the basic concepts and basic algorithms of Natural language processing.
  • Use existing natural language processing tools to conduct basic natural language processing, such as text normalization, named entity extraction, or syntactic parsing.
  • Use machine learning tools to build solutions for natural language processing problems.
  • Decompose a real-world problem into subproblems in natural language processing and identify potential solutions.

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A

Assessment

Assignment, Exam