BSc Data Science (Features: Data Science / Machine Learning / Data Mining / Big Data Analysis)
1072 (JS1072)
Local Places:
27 (For First Year and Advanced Standing I Entries; Tentative)*
Non-Local Places
(For Overall Direct Applications):
Around 400
PhD – Princeton University, USA
PhD - Simon Fraser University
+852 3442 7887
* for JUPAS and non-JUPAS admissions
Data Science DEEP
The programme provides essential trainings like quantitative knowledge, statistics, data mining technology and computing tools for emerging real world applications.
In an inter-professional setting, students are given the tools to build theoretical and methodological knowledge in data science, communication skills and ethic awareness. There are three flexible modules of advanced knowledge:
- Artificial Intelligence (Al)
- Social Media Analytics
- Statistical Learning
JUPAS Entrance Requirements
| JS1072 BSc Data Science | |
| HKDSE Subject | Minimum Level Required |
| English Language | Level 3 |
| Chinese Language | Level 3 |
| Mathematics | Level 3 |
| Citizenship and Social Development | Attained |
| Elective 1 | Level 3 |
| Elective 2 | Level 3 |
Notes:
- Besides Category A elective subjects, Mathematics extended modules (M1/M2) and “other languages” (at grade E or above) can also be used to meet the elective requirement. If students take both M1 and M2, they are counted as one subject only.
- Applied Learning subjects are not counted as elective subjects.
- For details of the alternative Chinese Language qualifications acceptable by the University for Non-Chinese Speaking (NCS) students, please click here.
Direct/ Non-JUPAS Applicants Entrance Requirements
To be considered for admission, you must satisfy the General Entrance Requirements.
First-Year Curriculum
First-Year Curriculum | Courses | No. of Credit Units | ||||||
| General Education | University Requirements | • GE1401 University English; and • Discipline-specific English; and • GE1501 Chinese Civilisation - History & Philosophy | 9 | |||||
| School Specified Requirements | School Specified GE courses for normative four-year degree:
| 9
| ||||||
| Distributional Requirements | At least one course from each of the three areas: Area 1: Arts and Humanities | 12 | ||||||
| School Requirement / Major Requirement | MA Linear Algebra with Applications | 4 | ||||||
| Major Requirement | SDSC2004 Data Visualization | 3 | ||||||
| Total No. of Credit Units: | 37 | |||||||
For details of the programme’s curriculum structure, please visit the ‘Undergraduate Catalogue’
The BSc Data Science aims to provide data science graduates with essential training in the quantitative methods, statistical analysis techniques, data mining technology and computing tools required for the effective use and analysis of big and complex data for real-world applications that involve making sense of complex data to realize planning and decision making. The programme develops strong and interdisciplinary training in the ability to build data analysis reasoning, communication skills and ethic awareness in realistic inter-professional settings for commercial or public policy problems in various disciplines.
The programme provides three flexible modules of advanced knowledge:
- Artificial Intelligence
- Social Media Analytics
- Statistical Learning
理學士(數據科學)：課程旨在為學生建立紥實的數據科學基礎和理論知識，並透過跨學科的培訓，提供如定量知識、統計學習、數據挖掘技術和電腦科學等課題，幫助學生融會貫通各領域和產業的專業需求，有效地分析和使用大數據和複雜資訊，建立分析推理能力、溝通技巧和道德意識。本課程具備以下三個專題讓學生針對個人興趣進行選修：
- 人工智能
- 社交媒體分析
- 統計學習
The unique power of data science knowledge and technology is gaining unprecedented attention in the job market, as big data analytics, data mining, machine learning and artificial intelligence become more and more relevant to mainstream industries. It is no wonder that data science has been heralded by the Harvard Business Review as one of the hottest fields in the 21st century. Data scientists solve some of the hardest problems that businesses face, and their work is relevant to almost all realms of business.
CityU’s BSc Data Science is a unique programme to offer students a rigorous theoretical and methodological knowledge of data science along with in-depth analysis and evaluation for applied problems. Graduates with such solid theoretical knowledge and rich practical experience capable of working alongside domain experts are in great demand in virtually all fields, including but not limited to the following.
• Finance and Banking
• Innovative Industry
• E-commerce
• IT and Software Companies
• Smart City
• Logistics and Transportation Systems
• Retail and Digital Marketing
• Power and Energy
• Healthcare and Medical Research
• Government and Public Organisations
• Consultancy
• Education and Research
• Small Business, Start-ups, Multi-industry Opportunities
Scholarships are available, please refer to the details at https://www.cityu.edu.hk/scholarship/.
The Department provides student exchange and internship opportunities to our students to gain international perspectives, global engagement and industry experience.
Students may choose between the overseas student exchange opportunities at world-leading institutions provided by the Department or the University. Paying the tuition at CityU, students will spend a study semester abroad and may transfer the academic credits earned at the host institution to fulfil the graduation requirement.
The Department also partners with premier corporates in a wide range of sectors to offer internship opportunities relevant to our majors. With these placements, students are expected to gain practical knowledge and hands-on experience in real-world applications.
