Bachelor of Science (Honours) in Applied Sciences (Statistics and Data Science) - Full-time
Bachelor of Science (Honours) in Applied Sciences (Statistics and Data Science) - Full-time
Programme Code
84048-SC (Full-time)
Medium of Instruction
English (except for subjects with Chinese requirements)
Tuition Fee
Normal Duration
2 years
Academic Division
Division of Science, Engineering and Health Studies
Remark
Programme curriculum and title are currently under review
Students and Alumni Stories
Programme Features
- Nurtures data analytics talents
- You will acquire knowledge of a range of data management and data analytics software, including SAS, Python, R, Microsoft Excel (VBA), Tableau, Microsoft Power Bl, and SQL Server
- You will be well prepared for career development through professional exam preparation workshops. Some students in the past obtained the credentials of SAS before graduation
- Opportunities to participate in internships. Past students have undergone training at PCCW Solutions, ICO Limited, lpsos and Nielsen
- You can select your elective subjects across multiple areas, e.g. A.I., Web Application Development and Management, and FinTech & Blockchain
Connect with us on IG
BSc (Hons) in Applied Sciences (Statistics and Data Science) |
|---|
Professional Recognition
Students can join the Hong Kong College of Community Health Practitioners (HKCCHP) as student members, and, upon graduation, can advance to the Associate Fellowship (AFHKCCHP) status.
Students are also eligible for exemption from Modules 1, 2, 3 and 5 of the Hong Kong Statistical Society's Graduate Diploma if they have completed the required specific subjects with satisfactory results.
Future Prospects
Career Prospect
- Graduates are able to pursue a wide range of careers, including Business Research Analyst, Data Analyst, Data Management Specialist and Statistical Analyst
- The average starting salary of graduates is around HK$16,900 in 2021
* Source: PolyU SPEED Graduate Employment Survey
Further Study Opportunities
- Past graduates have pursued postgraduate studies in famous local and overseas universities, such as The Hong Kong Polytechnic University, The Hong Kong Baptist University
Programme Structure
(The programme title and curriculum are currently under review)
Students are required to complete the following requirements with satisfactory results for an honours degree:
| Requirements | Minimum Credits | |
|---|---|---|
| General University Requirements (GUR) Note1 | 9 | |
| Cluster Area Requirements (CAR) | 2 subjects, 3 credits each | 6 |
| Service-Learning (SL) | 1 subject, 3 credits | 3 |
| Essential Components of General Education (non-credit bearing) | - | N/A |
| Discipline-Specific Requirements (DSR) Note2 (Please refer to the table below for details) | 51 – 60 | |
| Foundation | Up to 4 subjects, 1 non-credit-bearing; 3 credits each for others (for students from unrelated disciplines only) | 0 – 9 |
| Scheme Compulsory | 6 subjects, 3 credits each | 18 |
| Award-Specific Compulsory | 8 subjects, 3 credits each | 24 |
| Elective | 3 subjects, 3 credits each | 9 |
| Work-Integrated Education (WIE) Note3 | ||
| 300 hours of work-based learning experience | N/A | |
| Total | 60 – 78 | |
Discipline-Specific Requirements (DSR)
Scheme Compulsory (all 6 subjects)
- Business Communication in Chinese
- Effective Professional Communication in English
- Integrated Study (Applied Sciences)
- Management of Technology, Innovation and Entrepreneurship
- Professional Ethics and Social Responsibilities
- Research Methodology in Applied Sciences
Foundation (for students from unrelated disciplines only)
- Calculus
- Data Science with Programming
- Foundations of Data Science
- Statistical Data Analysis (non-credit-bearing)
Award-Specific Compulsory (all 8 subjects)
- Big Data and Cloud Analytics
- Data Structures and Algorithms
- Data Visualisation and Analytics
- Database Technologies and Management
- Decision Analysis with Python
- Forecasting and Applied Time Series Analysis
- Machine Learning for Data Mining
- Predictive Modeling
Elective# (any 3 subjects)
- Applied Probability Models
- Artificial Intelligence
- Computational Approaches to Language Analysis
- Computer Security
- Electronic Commerce Strategy and Implementation
- Financial Management for Non-finance Specialists
- FinTech and Blockchain
- Health Informatics and Healthcare 4.0
- Marketing Technologies
- Operations Research Methods
- Public Health and Epidemiology
- Simulation Models for Business
- Statistical Inference
- Survey Design and Analytics
- Web Application Development and Management
- Web Systems and Technologies
Entrance Requirements
Holder of a recognised Associate Degree, Higher Diploma or an equivalent qualification in related disciplines. Applicants from unrelated disciplines will also be considered and, if admitted, are required to take appropriate foundation subject(s).
Notes:
An applicant who is not a native speaker of English, and does not possess an Associate Degree or a Higher Diploma or an equivalent qualification for which English was the primary medium of instruction, is expected to fulfil the following minimum English language requirements:
i) An overall Band Score of 6.0 in the International English Language Testing System (IELTS); OR
ii) A Test of English as a Foreign Language (TOEFL) score of 80 for the Internet-based test / 550 for the paper-based test; OR
iii) Satisfactory results in other recognised English language assessments
Individual cases may be considered on their own merit, and applicants concerned may be required to take an additional 3-credit Adjunct English subject upon admission.
- An applicant who does not possess the above-mentioned qualification but has reached the age of 25 before 1 September, in the academic year in which he/she seeks admission, may apply as a mature applicant. He/she must demonstrate sufficient motivation, knowledge and potential to indicate a high probability of being able to complete the programme successfully. In addition, he/she may be required to take appropriate foundation subject(s).
- Applicants should have prior knowledge in linear algebra.
