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.
Tentative course offering schedule:
2022-23 Fall Term
- MSBD 5001 Foundations of Data Analytics*
- MSBD 5004 Mathematical Methods for Data Analysis*
- MSBD 5006 Quantitative Analysis of Financial Time Series
- MSBD 5012 Machine Learning
- MSBD 5015 Artificial Intelligence
- MSBD 5016 Deep Learning Meets Computer Vision: Practice and Applications
- MSBD 5017 Introduction to Blockchain Technology
- MSBD 6000F IoT and Mobile Sensing
- MSBD 6000L Database Systems
2022-23 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 5013 Statistical Prediction
- MSBD 5018 Natural Language Processing
- MSBD 6000X Reinforcement Learning with Financial Applications
- MSBD 6000Y Advanced Topics in AI and Big Data
*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 30 August 2022)
TPG – BDT