SIT330 - Natural Language Processing


2024 unit information

Enrolment modes: Trimester 1: Burwood (Melbourne), Online
Credit point(s): 1
EFTSL value: 0.125

SIT192 and SIT232 and one of SIT112, SIT114, or SIT307



Incompatible with:


Study commitment

Students will on average spend 150 hours over the trimester undertaking the teaching, learning and assessment activities for this unit.

This will include educator guided online learning activities within the unit site.

Scheduled learning activities - campus

1 x 3 hour seminar per week

Scheduled learning activities - online

Online independent and collaborative learning including 1 x 2 hour online seminar per week.


The widespread use of technology has allowed the creation of unlimited quantity of text data because people communicate almost everything in text language: webpages, social media posts, ads, emails, customer service, language translation, virtual agents, medical reports, etc. Thus, the need to exploit this unprecedented quantity of text data is critical for many companies and their business. This has led to the development of Document Processing techniques to extract valuable knowledge from this data, based on fast, effective and scalable information retrieval, text mining, and machine learning algorithms, which are at the heart of this unit focusing on descriptive, predictive, and prescriptive analytics of large-scale text data. In particular, this unit provides students with a deep understanding of the basic theories and techniques used to process large-scale of text document data to understand, search, identify, and extract information from semi-structured text documents. The unit will cover basic technologies for text document analysis, including information retrieval, search and indexing, information extraction, document classification, and natural language understanding.

Hurdle requirement

To be eligible to obtain a pass in this unit, students must meet certain milestones as part of the portfolio.

Unit Fee Information

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