Overview

This unit introduces students to core Natural Language Processing (NLP) concepts and techniques with a strong emphasis on generative AI. It equips students with practical skills in text data preprocessing, feature extraction, and the design, training, and evaluation of text classifiers. The unit also covers methods for visualising and interpreting NLP outputs, and exposes students to an advanced NLP technique commonly used in contemporary generative AI systems.

Requisites

Prerequisites
COS10009 Introduction to Programming

AND
100 credit points

Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date

Unit learning outcomes

Students who successfully complete this unit will be able to:

  1. Explain the concepts of computational linguistics in natural language processing
  2. Analyse and transform textual data into suitable representations for text analytics.
  3. Apply exploratory data analysis and visualisation techniques to textual data
  4. Design, implement and evaluate text classification models for natural language processing tasks

Teaching methods

All applicable locations

Type Hours per week Number of weeks Total (number of hours)
Live Online
Lecture		 2.00  12 weeks  24
On-Campus
Lecture		 2.00  12 weeks  24
Online
Directed Online Learning and Independent Learning		 1.00  12 weeks  12
Unspecified Activities
Independent Learning		 7.50  12 weeks  90
TOTAL     150

Assessment

Type Task Weighting ULOs
Assignment Individual 20 - 40% 1,2,3,4
Project Individual/Group 30 - 60% 1,2,3,4
Quizzes Individual 20 - 30% 1,3

Content

  • Basic string analysis techniques
  • Text wrangling, Web scrapping and pre-processing
  • Feature extraction
  • Text classifiers
  • Information retrieval evaluation
  • Visualisation
  • Advanced NLP Techniques, Deep Learning and Generative AI Applications.

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.