1. Core Courses (10 credit units, or 7 credit units for those exempted from taking SDSC2102) |
| Course Code | Course Title | Credit Units | Remarks |
|---|
| SDSC2001 | Python for Data Science | 4 | | | SDSC2102 | Statistical Methods and Data Analysis | 3 | Students who have completed MS2602 and have obtained a grade B- or above will be exempted from this course. | | SDSC3006 | Fundamentals of Machine Learning I | 3 | |
|
2. Semi-core courses (at least 3 credit units) |
| Course Code | Course Title | Credit Units | Remarks |
|---|
| SDSC2002 | Convex Optimization | 3 | | | SDSC2004 | Data Visualization | 3 | Take either SDSC2004 or GE2343 | | GE2343 | Data Visualization | 3 | Take either SDSC2004 or GE2343 | | SDSC3002 | Data Mining | 3 | | | SDSC3007 | Advanced Statistics | 3 | | | SDSC4016 | Fundamentals of Machine Learning II | 3 | |
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3. Electives (at least 3 credit units) |
| Course Code | Course Title | Credit Units |
|---|
| GE1356 | Introduction to Data Science | 3 | | SDSC2003 | Human Contexts and Ethics in Data Science | 3 | | SDSC2005 | Introduction to Computational Social Science | 3 | | SDSC3001 | Big Data: The Arts and Science of Scaling | 3 | | SDSC3004 | Computational Optimization | 3 | | SDSC3005 | Computational Statistics | 3 | | SDSC3010 | Digital Trace Analytics | 3 | | SDSC3011 | Social Data Processing and Modelling | 3 | | SDSC3013 | Introduction to Social Media Analytics | 3 | | SDSC3015 | Knowledge Graph and Cognitive Computing | 3 | | SDSC3016 | Social Network Analysis | 3 | | SDSC3017 | Game Theory and Its Application | 3 | | SDSC3027 | Smart Logistics and Transportation | 3 | | SDSC3105 | Bayesian Analysis | 3 | | SDSC4001 | Foundation of Reinforcement Learning | 3 | | SDSC4008 | Deep Learning | 3 | | SDSC4009 | Data Intelligence in Action | 3 | | SDSC4011 | Experimental Research for Social Media | 3 | | SDSC4018 | AI in Systematic Trading | 3 | | SDSC4019 | Stochastic Processes and Applications | 3 | | SDSC4110 | Statistical Design and Analysis of Experiments | 3 |
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