CS6493 - Natural Language Processing

Offering Academic Unit
Department of Computer Science
Credit Units
3
Course Duration
One Semester
Pre-requisite(s)
CS5481 Data Engineering or CS5487 Machine Learning: Principles and Practice or CS5489 Machine Learning: Algorithms and Applications or CS5491 Artificial Intelligence or SDSC5001 Statistical Machine Learning I or SDSC6001 Statistical Machine Learning II or SDSC8007 Deep Learning
Course Offering Term*:
Semester B 2024/25

* The offering term is subject to change without prior notice
 
Course Aims

This course introduces algorithms and techniques for natural language processing, from computational linguistics for text processing to information extraction for language understanding. The topics include statistical and neural based language modeling, word representation, pretrained language models such as BERT and large language models, such as GPT and Llama. Basic and advanced natural language processing tasks, such as machine translation dialog systems question answering, text classification/labeling/tagging, and knowledge graph will also be introduced.


Assessment (Indicative only, please check the detailed course information)
Continuous Assessment: 60%
Examination: 40%

For a student to pass the course, at least 30% of the maximum mark for the examination must be obtained.

Examination Duration: 2 hours
 
Detailed Course Information
CS6493.pdf