This course covers the fundamentals of software development, software process models, software system design, large-scale software system development, and software development environments. This course will focus on using Unified Modeling Language (UML) to perform analysis and design for Software System.
This course covers advanced and latest research issues in Natural Language Processing, including Sentiment Analysis, Topic Modeling, Text Clustering, Text Classification, Information Extraction, Dialogue Systems, Question Answering, Summarization, Text Generation, Knowledge Graphs, and Machine Translation. The discussion of these advanced topics will include some of the latest pre-trained models, such as BERT, Hugging Face, GPT, and ChatGPT.
在 2025年8月18日，10:50，Nur Azua Binti Wasis <nurazua.wasis@xmu.edu.my> 写道：
Sending on behalf of Dean/Deputy Dean/Assistant Dean/Head of Department/Head of Programme,School of Artificial Intelligence and Robotics (SAIR), Xiamen University MalaysiaDear Prof./Dr. Zhang Yingqian,Good day to you.The following courses have been assigned to you in the Academic Session: 2025/09.Course Information:
在 2025年8月18日，10:50，Nur Azua Binti Wasis <nurazua.wasis@xmu.edu.my> 写道：
Sending on behalf of Dean/Deputy Dean/Assistant Dean/Head of Department/Head of Programme,School of Artificial Intelligence and Robotics (SAIR), Xiamen University MalaysiaDear Prof./Dr. Zhang Yingqian,Good day to you.The following courses have been assigned to you in the Academic Session: 2025/09.Course Information:
The course aims to introduce algorithmic techniques that form the foundations of processing and analysing massive datasets of various forms. In particular, the course discusses how to pre-process massive datasets, efficiently store massive datasets, design fast algorithms for massive datasets, and analyse the performance of designed algorithms.
The course aims to introduce algorithmic techniques that form the foundations of processing and analysing massive datasets of various forms. In particular, the course discusses how to pre-process massive datasets, efficiently store massive datasets, design fast algorithms for massive datasets, and analyse the performance of designed algorithms.
Knowledge of artificial intelligence and related mathematics.
Machine learning problems and methods.