Course Schedule

Course Schedule

Students are required to complete a total of 30 credits of coursework, including 12 credits of core courses and 18 credits of elective courses.  Subject to approval, students may take a maximum of 6 credits of courses from the Master of Science in Information Technology. 

Note: It is not compulsory to complete the study credits within two terms. Students may adjust their study plans during their study terms.

Tentative course offering schedule:

2024-25 Fall Term

  • MSBD 5001    Foundations of Data Analytics*
  • MSBD 5004    Mathematical Methods for Data Analysis*
  • MSBD 5006    Quantitative Analysis of Financial Time Series
  • MSBD 5010    Image Processing and Analysis
  • MSBD 5012    Machine Learning
  • MSBD 5017    Introduction to Blockchain Technology
  • MSBD 5018    Natural Language Processing
  • MSBD 5020    Database Systems
  • MSBD 6000N  Understanding Large Language Models

2024-25 Spring Term

  • MSBD 5002    Data Mining and Knowledge Discovery*
  • MSBD 5003    Big Data Computing*
  • MSBD 5005    Data Visualization
  • MSBD 5007    Optimization and Matrix Computation
  • MSBD 5008    Introduction to Social Computing
  • MSBD 5009    Parallel Programming   
  • MSBD 5013    Statistical Prediction
  • MSBD 6000M  Reinforcement Learning with Financial Applications
  • MSBD 6000O  FinTech
  • MSBD 6000P   Big Data Algorithms

*Core course

All courses are offered subject to needs and availability. For the latest list of courses to be offered, visit Class Schedule & Quota.

For course details, please refer to Course Catalog.

(Updated on 4 February 2025)