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Unit of study_
COMP5046: Natural Language Processing
2026 unit information
This unit introduces the computational methods, methodological concepts, and theoretical ideas that underpin modern methods for processing natural language (such as English) using computers. NLP is used in a wide range of applications, including information retrieval and extraction; question answering; machine translation; code generation; dialogue; and classifying and clustering of documents. To achieve these, NLP systems perform a range of tasks using mathematical representations of language. In the context of these applications, the unit will explore common modelling methods, including heuristics, linear models, and neural networks, up to and including large language models (LLMs). The unit covers key ideas relevant to NLP from machine learning, statistics, linguistics, and data science. Students will implement NLP systems and evaluation metrics in labs and assignments. The unit will also investigate the annotation process for creating evaluation data for NLP systems. Students will annotate data as part of completing a real-world NLP task.
Unit details and rules
Managing faculty or University school:
Engineering
| Study level | Postgraduate |
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| Academic unit | Computer Science |
| Credit points | 6 |
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Prerequisites:
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None |
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Corequisites:
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None |
| Prohibitions:
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COMP4446 |
| Assumed knowledge:
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Knowledge of an OO programming language |
At the completion of this unit, you should be able to:
- LO1. apply basic linguistic knowledge to identify properties of text
- LO2. understand the internal architecture of language models including the purpose of each component
- LO3. implement and train machine learning based systems for solving natural language tasks
- LO4. evaluate the performance of natural language processing systems
- LO5. mplement and debug a large NLP system in a collaborative manner
- LO6. annotate data using appropriate quality control methods
- LO7. identify ethical concerns in NLP systems and ways to mitigate those issues
Unit availability
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