Bachelor of Science (Honours) Scheme in Data Science and Artificial Intelligence (JUPAS Code: JS3223)
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):
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BSc (Hons) Scheme in Data Science and Artificial Intelligence |
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Subject |
Credits |
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General University Requirements (GUR) (27 credits) |
COMP1004 Introduction to Artificial Intelligence and Data Analytics |
2 |
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|
MM1031 Introduction to Innovation and Entrepreneurship |
1 |
||||
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APSS1L01 Tomorrow’s Leaders |
3 |
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CAR-A Subject |
3 |
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CAR-M Subject |
3 |
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CAR-N Subject [recommend AF1605] |
3 |
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Service Learning Subject |
3 |
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LCR English I |
3 |
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LCR English II |
3 |
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LCR Chinese |
3 |
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Healthy Lifestyle |
0 |
||||
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Common Compulsory Subjects (22 credits) |
CMS1000 Computer and Mathematical Sciences Professionals in Society |
1 |
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AMA1702 Calculus |
3 |
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AMA1751 Linear Algebra |
3 |
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COMP1010 Computational Thinking and Problem Solving |
3 |
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COMP1011 Programming Fundamentals |
3 |
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DSAI1103 Principles of Data Science |
3 |
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DSAI2201 Data Structures and Algorithms |
3 |
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DSAI2202 Database Principles |
3 |
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Major Compulsory Subjects (38 credits)
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Data Science and Analytics (DSA) |
Financial Technology and Artificial Intelligence (FTAI) |
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Subject |
Credits |
Subject |
Credits |
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AMA2233 Data Analytics and Visualization |
3 |
AF1605 Introduction to Economics# |
3 |
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AMA2634 Introduction to Statistics |
3 |
AF2108 Financial Accounting or AF2111 Accounting for Decision Making |
3 |
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AMA2702 Multivariable Calculus |
3 |
AF3313 Business Finance |
3 |
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AMA3602 Applied Linear Models |
3 |
COMP2021 Object-oriented Programming |
3 |
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AMA3640 Statistical Inference |
3 |
COMP2322 Computer Networking |
3 |
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AMA3724 Further Mathematical Methods |
3 |
COMP3211 Software Engineering |
3 |
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AMA3820 Operations Research Methods |
3 |
COMP3334 Computer Systems Security |
3 |
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AMA4680 Statistical Machine Learning |
3 |
COMP4431 Artificial Intelligence |
3 |
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AMA4840 Decision Analysis |
3 |
DSAI4201 Data Protection and Security |
3 |
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AMA4850 Optimization Methods |
3 |
DSAI4202 E-Payment and Crypto Currency |
3 |
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DSAI4204 Data Mining and Data Warehousing |
3 |
DSAI4203 Machine Learning |
3 |
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DSAI4205 Big Data Analytics |
3 |
DSAI4206 Emerging Topics in FinTech |
3 |
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ELC3124 Professional English for Data Science and Analytics Students |
2 |
ELC3524 Professional Communication for Computing Students |
2 |
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Elective Subjects (25 credits) |
DSA Elective Subjects x 4 |
12 |
FTAI Elective Subjects x 2 |
6 |
|
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Finance Elective Subjects x 2 |
6 |
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Free Elective |
13 |
Free Elective |
13 |
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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 |
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Capstone Project (6 credits) |
DSAI4901 Capstone Project (6-credit two-semester subject) |
6 |
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WIE (2 training credits) |
DSAI3001 Work-Integrated Education (Training Credits) |
2 |
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Total |
120 + 2 (training credits) |
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# 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.
Curriculum Summary (for DSA with a Secondary Major)
To be eligible for a Secondary Major, you must have a cumulative GPA of 2.70 or above at the time of application for Secondary Major enrolment. The Secondary Major application period normally begins after the announcement of overall results for Semester Two of Year One. Your CGPA at the end of Semester Two of Year One will be used to determine your eligibility. If you are interested in pursuing a Secondary Major, please submit your application via eStudent > Application Forms > (AR164) Application for Major/Secondary Major/Double Major during the designated application period.
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Data Science and Analytics (DSA) with a Secondary Major in Innovation and Entrepreneurship (IE) |
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|
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)
|
AMA2233 Data Analytics and Visualization |
3 |
|
AMA2634 Introduction to Statistics |
3 |
|
|
AMA2702 Multivariable Calculus |
3 |
|
|
AMA3602 Applied Linear Models |
3 |
|
|
AMA3640 Statistical Inference |
3 |
|
|
AMA3724 Further Mathematical Methods |
3 |
|
|
AMA3820 Operations Research Methods |
3 |
|
|
AMA4680 Statistical Machine Learning |
3 |
|
|
AMA4840 Decision Analysis |
3 |
|
|
AMA4850 Optimization Methods |
3 |
|
|
DSAI4204 Data Mining and Data Warehousing |
3 |
|
|
DSAI4205 Big Data Analytics |
3 |
|
|
ELC3124 Professional English for Data Science and Analytics Students |
2 |
|
|
Professional Development Subject (2 credits) |
DSAI3911 Professionalism and Ethics in Data Science and AI |
2 |
|
Major Elective Subjects (12 credits) |
DSA Elective Subjects x 4 |
12 |
|
Capstone Project (6 credits) |
DSAI4901 Capstone Project (6-credit two-semester subject) |
6 |
|
Secondary Major Compulsory Subjects (21 credits) |
MM2021 Management and Organisation |
3 |
|
LGT3161/ MM3161 Creativity, Innovation and Entrepreneurship |
3 |
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MM2901/ MM2902 GBA Immersion or Field Study for Innovation Ecosystems |
3 |
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MM3162 Innovation and Entrepreneurship Colloquium |
3 |
|
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MM4393 Business Innovation Project |
3 |
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DSAI4001 Company Attachment (fulfill WIE Requirement) |
6 |
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Secondary Major Elective Subjects (15 credits) |
AMA3654 Survey Sampling |
3 |
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COMP3531 IT Entrepreneurship |
3 |
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IE General Elective Subject x 1 |
3 |
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IE Elective Subjects x 2 |
6 |
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WIE |
- |
- |
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DSA & IE Double Counting Subjects:
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(0-6) |
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Total |
137-143 |
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