Studying online (if an online offering is shown below)
There are now 2 possible online modes for units:
Units with modes Online timetabled and Online flexible are available for any student to self-enrol and study online.
Click on an offering mode for more details.
Unit Overview
- Description
Natural Language has been and will remain as the most preferred way to store and transfer knowledge. More than 80% of electronic data in modern societies are generated and stored in textual format. How to process unstructured text to extract useful insights and support actionable decision making and discover the hidden treasure of collective intelligence is of enormous value. In this unit, we start with traditional text processing techniques using Regular Expressions and discuss the needs of text processing and normalisation. We then introduce fundamental pipelines of natural language processing (NLP), including part-of-speech tagging and various ways of sentence parsing, with the aim of introducing traditional text feature collection techniques for higher-level tasks such as sentiment or document classification. Building on the understanding of the pros and cons of feature-based NLP pipeline approaches, the unit moves onto the modern approach of deep learning for NLP, focusing on word vector representation, neural language models, and recurrent neural networks for NLP. The unit situates the techniques around major NLP tasks, including information extraction, sentiment detection, dialogue systems and machine translation.
- Credit
- 6 points
- Offering
(see Timetable) Availability Location Mode Semester 2 UWA (Perth) Face to face - Outcomes
Students are able to (1) apply pre-processing techniques for textual data preparation; (2) build pipelines for core NLP tasks; (3) critically analyse different language models; (4) explain how vector representations of words can be obtained; (5) evaluate performance of NLP solutions, both traditional and neural; and (6) undertake core components of major NLP tasks.
- Assessment
Indicative assessments in this unit are as follows: (1) programming assignment and (2) final examination. Further information is available in the unit outline.
Student may be offered supplementary assessment in this unit if they meet the eligibility criteria.
- Unit Coordinator(s)
- Dr Wei Liu
- Unit rules
- Prerequisites
- Enrolment in HON-CMSSE Computer Science and Software Engineering)
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 62550 Master of Professional Engineering
or BH008 Bachelor of Advanced Computer Science [Honours]
or ( Bachelor of Engineering (Honours) or an associated Combined Degree
and 96 points
and Successful completion of
- Contact hours
- Lectures: 2-hours per week
Laboratories: 2-hours per week. - Note
- From 2025 this unit will be offered in semester 2 only.
- The availability of units in Semester 1, 2, etc. was correct at the time of publication but may be subject to change.
- All students are responsible for identifying when they need assistance to improve their academic learning, research, English language and numeracy skills; seeking out the services and resources available to help them; and applying what they learn. Students are encouraged to register for free online support through GETSmart; to help themselves to the extensive range of resources on UWA's STUDYSmarter website; and to participate in WRITESmart and (ma+hs)Smart drop-ins and workshops.
- Visit the Essential Textbooks website to see if any textbooks are required for this Unit. The website is updated regularly so content may change. Students are recommended to purchase Essential Textbooks, but a limited number of copies of all Essential Textbooks are held in the Library in print, and as an ebook where possible. Recommended readings for the unit can be accessed in Unit Readings directly through the Learning Management System (LMS).
- Contact hours provide an indication of the type and extent of in-class activities this unit may contain. The total amount of student work (including contact hours, assessment time, and self-study) will approximate 150 hours per 6 credit points.
Face to face
Predominantly face-to-face. On campus attendance required to complete this unit. May have accompanying resources online.
Online flexible
100% Online Unit. NO campus face-to-face attendance is required to complete this unit. All study requirements are online only. Unit is asynchronous delivery, with NO requirement for students to participate online at specific times.
Online timetabled
100% Online Unit. NO campus face-to-face attendance is required to complete this unit. All study requirements are online only. Unit includes some synchronous components, with a requirement for students to participate online at specific times.
Online Restricted
Not available for self-enrolment. Students access this mode by contacting their student office through AskUWA. 100% Online Unit.
NO campus face-to-face attendance. All study and assessment requirements are online only. Unit includes some timetabled activities, with a requirement for students to participate online at specific times. In exceptional cases (noted in the Handbook) students may be required to participate in face-to-face laboratory classes when a return to UWA’s Crawley campus becomes possible in order to be awarded a final grade.
External
No attendance or regular contact is required, and all study requirements are completed either via correspondence and/or online submission.
Off-campus
Regular attendance is not required, but student attends the institution face to face on an agreed schedule for purposes of supervision and/or instruction.
Multi-mode
Multiple modes of delivery. Unit includes a mix of online and on-campus study requirements. On campus attendance for some activities is required to complete this unit.