Curriculum Structure

The normative study period of part-time students is 2 years.
Students are required to complete not fewer than 75 credits nor more than 84* credits of courses selected from the syllabus which must include capstone experience.
Course Category |
No. of Courses |
No. of Credits |
---|---|---|
Discipline Courses |
≥ 8 |
Not less than 51 |
Elective Courses # |
≤ 2 |
Not less than 12 |
Capstone Experience |
Project |
12 |
|
Total: |
75 to 84 * |
# Subject to University approval
* Most courses in the curriculum has 6 credits. However, courses offered by Faculty of Law has 9 credits. Candidates who choose one, two, or three 9-credit courses, in addition to the Disciplinary compulsory course in Law, are required to complete 78, 81 or 84 credits respectively for satisfying the curriculum requirement.
Candidates shall select courses in accordance with the regulations of the degree. Candidates must complete a Project and 10 courses with the following requirements.
# Subject to University approval
List-A Disciplinary compulsory courses (3 courses) |
|||
Discipline |
Course |
||
Technology |
FITE7409 # Blockchain and Cryptocurrency (6 credits) or COMP7408 # Distributed Ledger and Blockchain Technology (6 credits) |
||
Finance |
MFIN7002 Investment Analysis and Portfolio Management (6 credits) |
||
Law |
LLAW6093 Regulation of Financial Markets (9 credits) |
# Candidates holding a non-computer science major should select FITE7409 Blockchain and Cryptocurrency while candidates holding a computer science major should select COMP7408 Distributed Ledger and Blockchain Technology.
List-B Disciplinary courses |
|||
List-B-1 |
List-B-2 |
||
COMP7802 Introduction to Financial computing (6 credits) |
FITE7407 Securities Transaction Banking (6 credits) |
||
COMP7906 Introduction to Cyber Security (6 credits) |
FITE7410 Financial Fraud Analytics (6 credits) |
||
ECOM6016 Electronic Payment Systems (6 credits) |
STAT6013 Financial Data Analysis (6 credits) |
List-C Disciplinary courses # |
|||
List-C-1 |
List-C-2 |
||
FITE7405 Techniques in Computational Finance (6 credits) |
ECOM6023 E-financial Services (6 credits) |
||
FITE7406 Software Development for Quantitative Finance (6 credits) |
ECOM7126 Machine Learning for Business and E-commerce (6 credits) |
||
FITE7801 Topics in Financial Technology (6 credits) |
IMSE7310 Financial Engineering (6 credits) |
||
COMP7103 Data Mining (6 credits) |
LLAW6046 Privacy and Data Protection (9 credits) |
||
COMP7305 Cluster and Cloud Computing (6 credits) |
LLAW6126 E-Finance: Law, Compliance and Technology Challenges (9 credits) |
||
COMP7404 Computational Intelligence and Machine Learning (6 credits) |
LLAW6256 Law of Anti-money Laundering and Counter-terrorist Financing and Compliance Issues (9 credits) |
||
COMP7409 Machine Learning in Trading and Finance (6 credits) |
MFIN7034 ^ Machine Learning and Artificial Intelligence in Finance (6 credits) or MFIN7037 ^ Quantitative Trading (6 credits) |
||
DASC7606 Deep Learning (6 credits) |
STAT6015 Advanced Quantitative Risk Management and Finance (6 credits) |
||
STAT8020 Quantitative Strategies and Algorithmic Trading (6 credits) |
|
# Subject to University approval
^ Candidates can only select either MFIN7034 Machine Learning and Artificial Intelligence in Finance or MFIN7037 Quantitative Trading.
Capstone requirement |
FITE7001 Project (12 credits) |