Natural Language Processing

Undergraduate | 2026

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Mode
Mode
Your studies will be on-campus, and may include some online delivery
On campus
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Area/Catalogue
MATH X415
Course ID icon
Course ID
208316
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Campus
Adelaide City Campus
Level of study
Level of study
Undergraduate
Unit value icon
Unit value
6
Course owner
Course owner
Adelaide University
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Course level
4
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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.
Yes
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University-wide elective course
Yes
Single course enrollment
Single course enrolment
Yes
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Note:
Course data is interim and subject to change

Course overview

This course aims to equip learners with the knowledge and skills to analyse textual datasets. Building upon concepts of data science practice, this course will look at the challenges and methods used for textual datasets. By examining the methods of tokenization, sentiment analysis and topic modelling the course shows how the patterns in textual data can be identified. This course aligns with the program's intent to provide a comprehensive understanding of methods to find patterns in real datasets.

Course learning outcomes

  • Demonstrate an ability to read text into R and then prepare it with tokenisation, stop words and word embedding
  • Understand the importance of representative datasets and the ethics of using text from social sources
  • Demonstrate the ability to apply sentiment analysis and topic modelling to real datasets
  • Demonstrate the ability to interpret the output from sentiment analysis and topic modelling

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A

Degree list
The following degrees include this course