This course covers some of the linguistic and algorithmic foundations of natural language processing. The aim of the course is to equip students for more advanced NLP techniques.
AIT202 Methods and Applications of Deep Learning
AIT403 Advanced Data Analysis course is designed for final-year data science students to deepen their understanding of key analytical techniques, from handling big data to applying advanced machine learning and clustering methods. In today’s data-driven world, the ability to analyze large datasets and extract meaningful insights is crucial.
This course covers advanced and latest research issues on Natural Language Processing, including Sentiment Analysis, Topic Modeling, Text Clustering, Text Classification, Information Extraction, Dialogue System, Question Answering, Summarization, Text Generation, Knowledge Graph, and Machine Translation. The discussion of these advanced topics will include some of the latest pre-trained models, such as: BERT, Hugging Face, GPT, ChatGPT, etc.
This course covers fundamental of software development, software process models, software system design, large-scale software system development, and software development environment.
The course is to introduce text analytics for product review analysis using sentiment analysis and aspect extraction. The students will learn how to use natural language processing techniques such as sentence splitting, tokenisation, stop word removal, stemming, normalisation, etc. to process and transform text content into a representation that can be used in machine learning algorithms. The student will acquire the knowledge and skills to produce data analytics from text preprocessing, sentiment analysis, aspect extraction, and data visualisation to support product review analysis.
The course aims to introduce students to the fundamental concepts of artificial intelligence (AI). It will cover topics such as knowledge representation, search strategies, machine learning and deep learning techniques. By the end of the course, students will have a solid understanding of core AI principles, key problem-solving approaches, and the practical applications of AI.