Bachelor of Science (Honours) Scheme in Data Science and Artificial Intelligence (JUPAS Code: JS3223)

Curriculum

All admitted students will embark on a Common Year One curriculum within the Faculty of Computer and Mathematical Sciences.
Years Two-Four: Students are streamed into one of the two Majors under the Scheme based on their individual preferences. They continue to complete subjects required by the Major.

Scheme Curriculum Summary (for normal intake):

	BSc (Hons) Scheme in Data Science and Artificial Intelligence
	Subject				Credits
General University Requirements (GUR) (27 credits)	COMP1004 Introduction to Artificial Intelligence and Data Analytics				2
	MM1031 Introduction to Innovation and Entrepreneurship				1
	APSS1L01 Tomorrow’s Leaders				3
	CAR-A Subject				3
	CAR-M Subject				3
	CAR-N Subject [recommend AF1605]				3
	Service Learning Subject				3
	LCR English I				3
	LCR English II				3
	LCR Chinese				3
	Healthy Lifestyle				0
Common Compulsory Subjects (22 credits)	CMS1000 Computer and Mathematical Sciences Professionals in Society				1
	AMA1702 Calculus				3
	AMA1751 Linear Algebra				3
	COMP1010 Computational Thinking and Problem Solving				3
	COMP1011 Programming Fundamentals				3
	DSAI1103 Principles of Data Science				3
	DSAI2201 Data Structures and Algorithms				3
	DSAI2202 Database Principles				3
Major Compulsory Subjects (38 credits)	Data Science and Analytics (DSA)		Financial Technology and Artificial Intelligence (FTAI)
	Subject	Credits	Subject		Credits
	AMA2233 Data Analytics and Visualization	3	AF1605 Introduction to Economics^#		3
	AMA2634 Introduction to Statistics	3	AF2108 Financial Accounting or AF2111 Accounting for Decision Making		3
	AMA2702 Multivariable Calculus	3	AF3313 Business Finance		3
	AMA3602 Applied Linear Models	3	COMP2021 Object-oriented Programming		3
	AMA3640 Statistical Inference	3	COMP2322 Computer Networking		3
	AMA3724 Further Mathematical Methods	3	COMP3211 Software Engineering		3
	AMA3820 Operations Research Methods	3	COMP3334 Computer Systems Security		3
	AMA4680 Statistical Machine Learning	3	COMP4431 Artificial Intelligence		3
	AMA4840 Decision Analysis	3	DSAI4201 Data Protection and Security		3
	AMA4850 Optimization Methods	3	DSAI4202 E-Payment and Crypto Currency		3
	DSAI4204 Data Mining and Data Warehousing	3	DSAI4203 Machine Learning		3
	DSAI4205 Big Data Analytics	3	DSAI4206 Emerging Topics in FinTech		3
	ELC3124 Professional English for Data Science and Analytics Students	2	ELC3524 Professional Communication for Computing Students		2
Elective Subjects (25 credits)	DSA Elective Subjects x 4	12	FTAI Elective Subjects x 2		6
			Finance Elective Subjects x 2		6
	Free Elective	13	Free Elective		13
Professional Development Subject (2 credits)	DSAI3911 Professionalism and Ethics in Data Science and AI	2	DSAI3911 Professionalism and Ethics in Data Science and AI		2
Capstone Project (6 credits)	DSAI4901 Capstone Project (6-credit two-semester subject)				6
WIE (2 training credits)	DSAI3001 Work-Integrated Education (Training Credits)				2
Total				120 + 2 (training credits)

# If students use AF1605 to satisfy the CAR-N requirement (i.e., AF1BN02), they will be required to take another 3-credit free elective subject to make up for the total credit requirement.

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