Master of Science in Artificial Intelligence and Big Data Computing (62037-FAI/PAI)

Study Pattern

Each subject takes place once a week in the evening over a 13-week semester. Full-time students normally take five subjects in a semester, whereas part-time students usually take two or three subjects. Some subjects may be offered during the summer to provide students with greater flexibility in designing their own study plan.

Students are required to complete 31 credits. All subjects carry 3 credits, unless otherwise specified. Students must complete the following:

AIBD programme core (Programme-Core) subjects: 3 credits
Artificial Intelligence core (AI-Core) subjects: 6 credits
Big Data Computing core (BD-Core) subjects: 6 credits
Compulsory dissertation: 9 credits
Electives, BD-Core, AI-Core, and/or Programme-Core subjects: 6 credits
Academic Integrity and Ethics (AIE) subject: 1 credit

[Tuition fees will not be charged for the 1-credit AIE subject.]

List of Subjects

Below is the table summarising the core and elective subjects. The table is subjected to finalization. Affected students will be informed if there are further changes.

AIBD programme core (Programme-Core) Subjects

DSAI5201 Artificial Intelligence and Big Data Computing in Practice

DSAI5202 Emerging Topics in Artificial Intelligence and Big Data Computing

Artificial Intelligence core (AI-Core) Subjects

COMP5423 Natural Language Processing

COMP5511 Artificial Intelligence Concepts

COMP5523 Computer Vision and Image Processing

COMP5541 Machine Learning and Data Analytics

DSAI5203 Brain-inspired Computing

Big Data Computing core (BD-Core) Subjects

COMP5111 Database Systems and Management

COMP5112 Data Structures and Database Systems

COMP5152 Advanced Data Analytics

COMP5434 Big Data Computing

DSAI5101 Statistical Data Mining

Compulsory Dissertation

DSAI5902 Dissertation for Artificial Intelligence & Big Data Computing

Elective Subjects

AMA567 Quantum Computing for Data Science

COMP5221 Software Project Management

COMP5355 Cyber and Internet Security

COMP5574 Computational Economics and Algorithms

COMP5575 Advanced Techniques for High-Dimensional Data Management and Analytics

DSAI5102 Principles of Data Science

DSAI5104 Optimization for Machine Learning (subject to approval)

Academic Integrity and Ethics (AIE) Subject

EEE5T03 Engineering Ethics and Academic Integrity

All subjects are offered at the discretion of subject offering departments, depending on students’ demand and resources available.

Programme Requirement Document

2024/25 Cohort [restricted access for DSAI designated staff/students]

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