The programme aims to equip students with cutting-edge methodologies and skills in data analytics and artificial intelligence. By acquiring these competencies, students will be able to apply advanced technologies to transform business needs into real-world IT solutions.
The programme includes 14 units of core courses and 15 units of elective courses.
The elective courses are organized into: (i) Data Analytics, (ii) Artificial Intelligence, and (iii) 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 | |
| Ethics of Data Analytics and Artificial Intelligence | 1 | |
| Elective Courses | 15 | |
| Stream 1 – Data Analytics | ||
| Innovative Laboratory | 3 | |
| Data Security and Privacy | 3 | |
| Blockchain and Cryptocurrenciesx | 3 | |
| Special Topics in Data Analytics | 3 | |
| Financial Technology | 3 | |
| Database Systems and Administration | 3 | |
| Data Mining and Knowledge Discovery | 3 | |
| Business Intelligence | 3 | |
| Visual Analytics and Decision Support | 3 | |
| Big Data Analytics | 3 | |
| Cloud Computing | 3 | |
| Audio and Speech Processing | 3 | |
| Stream 2 – Artificial Intelligence | ||
| Natural Language Processing and Large Language Models | 3 | |
| Computer Vision | 3 | |
| Innovative Laboratory | 3 | |
| Prompt Engineering for Generative AI | 3 | |
| Blockchain and Cryptocurrencies | 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 | |
| Audio and Speech Processing | 3 | |
| Autonomous Robotics | 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 | |
| Ethics of Data Analytics and Artificial Intelligence | 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 | |
| Ethics of Data Analytics and Artificial Intelligence | 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.