The programme focuses on the concepts and practices of information systems and covers three themes for advanced information systems (namely, Data Analytics, Artificial Intelligence and Intelligent Information Systems). Students learn solid concepts and gain hands-on skills in these themes, so that they could apply these concepts and skills to solve real-world information system problems.
The programme includes 14 units of core courses and 15 units of elective courses.
The elective courses are organized into three streams, namely, Data Analytics, Artificial Intelligence and Intelligent Information Systems and MSc Practicum & Research. Students can select elective courses freely.
| unit(s) | unit(s) | |
|---|---|---|
| Core Courses | 14 | |
| Artificial Intelligence | 3 | |
| Python for Data Analytics and Artificial Intelligence | 3 | |
| Quantitative Methods for Data Analytics and Artificial Intelligence | 3 | |
| Principles and Practices of Data Analytics | 3 | |
| IT Forum | 1 | |
| IT Project Skills | 1 | |
| Elective Courses | 15 | |
| Stream 1 – Data Analytics | ||
| Data Security and Privacy | 3 | |
| Special Topics in Data Analytics | 3 | |
| Database Systems and Administration | 3 | |
| Data Mining and Knowledge Discovery | 3 | |
| Business Intelligence | 3 | |
| Big Data Analytics | 3 | |
| Stream 2 – Artificial Intelligence | ||
| Natural Language Processing and Large Language Models | 3 | |
| Computer Vision | 3 | |
| Special Topics in Artificial Intelligence | 3 | |
| Recommender Systems | 3 | |
| Machine Learning | 3 | |
| Web Intelligence and Its Applications | 3 | |
| Data Mining and Knowledge Discovery | 3 | |
| Business Intelligence | 3 | |
| Prompt Engineering for Generative AI | 3 | |
| Stream 3 – Intelligent Information Systems | ||
| Innovative Laboratory | 3 | |
| Special Topics in Intelligent Information Systems | 3 | |
| Blockchain Technology | 3 | |
| Web and Mobile Programming | 3 | |
| Financial Technology | 3 | |
| Health Information Systems: Architecture and Technologies | 3 | |
| Visual Analytics and Decision Support | 3 | |
| Cloud Computing | 3 | |
| MSc Practicum & Research | ||
| MSc Practicum | 3 | |
| MSc Research I | 3 | |
| MSc Research II | 3 | |
| 29 | ||
Remarks: There may be minor revisions to the curriculum.
The programme is offered in both one-year full-time mode and two-year part-time mode. Most classes are conducted on weekday nights at 6:30-9:20pm while a few classes, assessment activities and make-up classes may be conducted on Saturday daytime. In this manner, both full-time and part-time students can attend these classes/activities.
For full-time study, the normal study schedule is as follows:
| Semester 1 (units) | Semester 2 (units) | |
|---|---|---|
| First Year | ||
| Python for Data Analytics and Artificial Intelligence | 3 | |
| Principles and Practices of Data Analytics | 3 | |
| Artificial Intelligence | 3 | |
| Quantitative Methods for Data Analytics and Artificial Intelligence | 3 | |
| IT Project Skills | 1 | |
| IT Forum | 1 | |
| Elective Courses | 15 |
For part-time study, the normal study schedule is as follows:
| Semester 1 (units) | Semester 2 (units) | |
|---|---|---|
| First Year | ||
| Principles and Practices of Data Analytics | 3 | |
| Quantitative Methods for Data Analytics and Artificial Intelligence | 3 | |
| IT Project Skills | 1 | |
| Elective Courses | 9 | |
| Second Year | ||
| Python for Data Analytics and Artificial Intelligence | 3 | |
| Artificial Intelligence | 3 | |
| IT Forum | 1 | |
| Elective Courses | 6 |
The medium of instruction is English. All teaching and learning materials are in English.