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Data Science
Advanced Standing I
Major
Data Science
數據科學
Degree / Award Title
Bachelor of Science in Data Science
理學士(數據科學)
Offering Academic Unit
School of Data Science
Normal Period of Study
3 years
Maximum Period of Study
6 years
Credit Units Required for Graduation
90 credit units
Note: The following curriculum information is subject to periodic review and changes.

GE Requirements (21 credit units)Catalogue Term : Semester A 2023/24



  Credit Units
University Requirements GE1401 University English 3
GE2401 English for Science 3
GE1501 Chinese Civilisation - History and Philosophy 3
Distributional Requirements Take 2 courses from two different distributional areas:

Area 1: Arts and Humanities
Area 2: Study of Societies, Social and Business Organisations
Area 3: Science and Technology

Visit the GE website for more course information.
6
School-specified Courses CS1315 Introduction to Computer Programming 3
Take any course NOT within the Major requirement (including core courses and electives) 3

College / School Requirements (18 credit units)Catalogue Term : Semester A 2023/24


Course CodeCourse TitleCredit Units
CS3402Database Systems3
MA1503Linear Algebra with Applications4
MA2508Multi-variable Calculus4
MA2510Probability and Statistics3
SDSC2001Python for Data Science4

Major Requirements (45 credit units)Catalogue Term : Semester A 2023/24



Notes:

  • Major-based students admitted in 2023 will follow the Major Requirements of Catalogue Term Semester A 2023/24.
  • School-based students admitted in 2023 will follow the Major Requirements of Catalogue Term Semester A 2024/25, when they declare a home major next year.

1. Core Courses (33 credit units)

Course CodeCourse TitleCredit Units
SDSC2002Convex Optimization3
SDSC2003Human Contexts and Ethics in Data Science3
SDSC2004Data Visualization3
SDSC2005Introduction to Computational Social Science3
SDSC2102Statistical Methods and Data Analysis3
CS2334Data Structures for Data Science3
CS3273Data Protection and System Security3
SDSC3006Fundamentals of Machine Learning I3
SDSC3007Advanced Statistics3
SDSC4116Data Science Capstone6

2. Electives (12 credit units) - Must earn at least 12 credit units from B4 level courses

Course CodeCourse TitleCredit UnitsRemarks
GE2339Smart City - a Systems Engineering Perspective3B2 level / Artificial Intelligence Module
IS2505e-Business3B2 level / General
CS3201Computer Networks3B3 level / General
EE3919Medical Imaging and Signal Processing3B3 level / General / Inactive
LT3233Computational Linguistics3B3 level / General
SDSC3001Big Data: The Arts and Science of Scaling3B3 level / Artificial Intelligence Module *
SDSC3002Data Mining3B3 level / Artificial Intelligence Module and Statistical Learning Module
SDSC3003Blockchain3B3 level / General
SDSC3004Computational Optimization3B3 level / Statistical Learning Module
SDSC3005Computational Statistics3B3 level / Statistical Learning Module
SDSC3008Systems Dynamics and Control3B3 level / Artificial Intelligence Module
SDSC3009Behavioural Analytics3B3 level / Social Media Analytics Module
SDSC3010Digital Trace Analytics3B3 level / Social Media Analytics Module
SDSC3011Social Data Processing and Modelling3B3 level / Social Media Analytics Module
SDSC3013Introduction to Social Media Analytics3B3 level / Social Media Analytics Module *
SDSC3014Introduction to Sharing Economy3B3 level / General
SDSC3015Knowledge Graph and Cognitive Computing3B3 level / Artificial Intelligence Module
SDSC3016Social Network Analysis3B3 level / Social Media Analytics Module
SDSC3017Game Theory and Its Application3B3 level / Artificial Intelligence Module
SDSC3018Introduction to Internet of Things3B3 level / General
SDSC3019Introduction to Networked Life and Data Science3B3 level / General
SDSC3022Financial Data Analytics for Investments3B3 level / General
SDSC3023Data Science Applications in Portfolio Risk Analysis3B3 level / General
SDSC3060Operations Research3B3 level / General
SDSC3105Bayesian Analysis3B3 level / Statistical Learning Module *
COM4511Social Media and Communication3B4 level / Social Media Analytics Module
CS4186Computer Vision and Image Processing3B4 level / General
CS4286Internet Security and e-Commerce Protocols3B4 level / General
CS4296Cloud Computing3B4 level / General
CS4480Data-Intensive Computing3B4 level / General
CS4486Artificial Intelligence3B4 level / Artificial Intelligence Module
CS4487Machine Learning3B4 level / Artificial Intelligence Module
SDSC4001Foundation of Reinforcement Learning3B4 level / Artificial Intelligence Module and Statistical Learning Module
SDSC4008Deep Learning3B4 level / Artificial Intelligence Module and Statistical Learning Module
SDSC4009Data Intelligence in Action3B4 level / Artificial Intelligence Module
SDSC4010Projects in Data Science (research)3B4 level / General
SDSC4011Experimental Research for Social Media3B4 level / Social Media Analytics Module
SDSC4016Fundamentals of Machine Learning II3B4 level / Artificial Intelligence Module and Statistical Learning Module *
SDSC4018AI in Systematic Trading3B4 level / Artificial Intelligence Module
SDSC4019Stochastic Processes and Applications3B4 level / Statistical Learning Module
SDSC4026Systems Modelling and Simulation3B4 level / General
SDSC4107Financial Engineering and Analytics3B4 level / General
SDSC4110Statistical Design and Analysis of Experiments3B4 level / Statistical Learning Module

Remark: To complete the study of one module, students are required to take the module required course (with * mark) AND take at least 4 courses in total in this module.
 

3. Optional Electives for all normative 4-year degree and ASI

Students may choose to enrol in the below course(s) to enrich their study.
Course CodeCourse TitleCredit UnitsRemarks
SDSC0001Internship0
SDSC0002Internship0
SDSC0003Internship0
SDSC0004Internship0
SDSC3080Internship3