Sept 2023 Entry
Programme code: JS30204 years (including 1 year with common curriculum)
At least 124, depending on the student's qualifications (plus 2 training credits)
Scheme Leader
Dr Sze Nung-sing, Raymond
BSc, MPhil, PhD
BSc (Hons) in Data Science and Analytics
Programme Leader
Dr Pong Ting-kei
BSc, MPhil, PhD
Deputy Programme Leader
Dr Wong Kin Yau, Alex
BSc, MPhil, PhD
Assistant Programme Leader
Dr Tai Hoi-lun, Allen
BSc, MPhil, PhD
BSc (Hons) in Investment Science and Finance Analytics
Programme Leader
Dr Sze Nung-sing, Raymond
BSc, MPhil, PhD
Deputy Programme Leader
Dr He Daihai
PhD
Assistant Programme Leader
Mr Leung Man Kin, Adam
BSc, MPhil
This 4-year full-time scheme is designed to provide students with solid training in mathematical, statistical and computer programming skills, with special emphasis on applications in investment and finance analytics or data science and analytics. This Scheme comprises the following two undergraduate Major programmes:
BSc (Hons) in Data Science and Analytics
This Major focuses on training graduates with expertise that cuts across the core disciplines of mathematics, statistics and computer science. It emphasises the critical arc from data to information, information to knowledge, and knowledge to decision making.
BSc (Hons) in Investment Science and Finance Analytics
This Major is designed to provide students with strong mathematical and statistical skills and a thorough understanding of their applications in the world of modern investment and finance analytics.
All students admitted to the Scheme take a common set of subjects in their first year and select one of the Majors under the Scheme in their second year.
Year One: Students study the General University Requirement (GUR) subjects and subjects common to the Scheme, such as Calculus, Multivariable Calculus, Linear Algebra, Probability & Distributions, and Programming Fundamentals.
Year Two: Students are streamed into one of the two Majors under the Scheme based on their individual preferences. They continue to complete subjects common to the Scheme, as covered by the following modules: Introduction to Statistics, Database System, Principles of Programming, Applied Linear Models and Operations Research Methods. Students start to study major discipline-specific compulsory subjects in Data Science and Analytics or Investment Science and Finance Analytics.
Year Three: Students are expected to complete most of the major discipline-specific compulsory subjects, including Statistical Machine Learning, Big Data Analytics, Decision Analysis, and Optimization Methods for the Data Science and Analytics programme, and Corporate Finance, Theory of Interest and Portfolio Analysis, Investments, Derivative Pricing, and Econometrics for the Investment Science and Finance Analytics programme.
Year Four: Students have the flexibility to choose their major discipline-specific elective subjects from a large pool in the fields of statistics, data science, computing science, finance and investment, health and medical informatics and urban informatics. They also complete a Capstone Project in which they tackle a problem or research topic in data science/finance analytics/statistics/applied mathematics, consolidating the discipline-specific knowledge, conceptual understanding, and generic skills they have developed through different stages of the programme.
For details, please refer to the following website: www.polyu.edu.hk/ama/ug.
The option of a Secondary Major in AI and Data Analytics (AIDA) is available to the students of the BSc (Hons) in Investment Science and Finance Analytics. The option of a Secondary Major in Innovation and Entrepreneurship (IE) is available to the students of the BSc (Hons) in Data Science and Analytics.
Selection Criteria
Studying a Secondary Major is not mandatory. Only students with a cumulative GPA of 2.70 or above may be considered for Secondary Major enrolment. Each Secondary Major may stipulate additional selection criteria for admission. Students must apply to and obtain approval from the programme-offering Department, no later than the commencement of the second year of study, to be admitted to the Secondary Major.
Credit Requirements
The students of the BSc (Hons) in Data Science and Analytics (DSA) with a Secondary Major in Innovation and Entrepreneurship (IE) are required to complete 148 credits for graduation. The students of the BSc (Hons) in Investment Science and Finance Analytics (ISFA) with a Secondary Major in AI and Data Analytics (AIDA) are required to complete 153 credits for graduation.
*Including 2 training credits
^Students taking the ISFA + AIDA route may accrue up to 12 credits for double counting from their Major/GUR subjects, including the Integrated Capstone Project (6 credits), towards the Secondary Major.
Professional Accreditation
Graduates of the DSA + IE stream are accredited by the Hong Kong Statistical Society and Royal Statistical Society of the UK.
Graduates of the ISFA + AIDA stream are also accredited by the Hong Kong Securities and Investment Institute, Hong Kong Statistical Society (subject to confirmation), and Royal Statistical Society of the UK (subject to confirmation).
Career Prospects
The Scheme is designed to develop students’ analytical, critical thinking, problem-solving and communication skills, nurturing an outlook and methodology that equip graduates to pursue a variety of careers in fields such as telecoms, information technology, market research, manufacturing, pharmaceuticals, investment banking, fund management, risk management, and financial product development and pricing.
Professional Recognition
On the completion of the programme, graduates are expected to receive partial exemption from the professional assessment of:
1. The Hong Kong Securities and Investment Institute
2. The Hong Kong Statistical Society
3. The Royal Statistical Society of the UK
BSc (Hons) in Data Science and Analytics: 2 & 3
BSc (Hons) in Investment Science and Finance Analytics: 1* (2 & 3 subject to confirmation)
*For details, please refer to the following website: https://www.polyu.edu.hk/ama/study/ug/ds_scheme/.
The ISFA programme is affiliated with the CFA Institute University Affiliation Program. This affiliation demonstrated that the ISFA curriculum is closely tied to professional practice and is well-suited to preparing students to sit for the CFA examinations. The curriculum has been acknowledged as covering at least 70% of the CFA Program Level I Candidate Body of Knowledge (CBOK) topics. Through participation in the affiliation program, CFA student scholarship is available to ISFA students.
Please click here to view the entrance requirements for non-JUPAS applicants.
Other Information
For further programme information, please contact
the General Office (tel.: 2766 6946; email: ds.info@polyu.edu.hk)
In the past 4 year, I have had a memorial university life with AMA and gained insights from various perspectives. This programme consolidates my concepts on basic mathematics theories and algorithm. I also learned statistical and financial models in senior years. Through practical application, we understand how real-life situations can be explained or diverse from models. Besides, the knowledge from computing courses also enables me to work more effectively on data handling. Living in big data era, catching up with the trend of data processing is essential and would surely benefit us in many aspects such as technology development or even in financial industry. AMA’s professors and officers are very friendly. We as students always have chance to express our opinions towards curriculum design of our study programme. We are encouraged to join workshops or training courses offered by Department, such as Advanced Excel or Python. Moreover, exchange study and internship opportunities are always opened for us to strengthen our learning experience and find our true selves. Many of us have identified our career path after taking internship. I plan to pursue further study and gained support from professors for taking a Master’s degree.
Studying in AMA is unforgettable to me. In addition to pursuing knowledge, I also gain precious friendships and memories from taking the role of President of the Departmental Society of Applied Mathematics (DSAM). Having the chance to organize different student events and make contribution to my fellow classmates is not only an honor but also giving me a sense of belonging to AMA. All of these memories have definitely made my university life a lot more fruitful. Heidi Wan |  |
 | AMA offers a diverse learning opportunities e.g. computer programming workshops and internship. This programme has well prepared me with Data Analytic skills which greatly support my job as a Customer Value Management Officer in bank upon my graduation. Cheryl Wong |
I’m grateful for the opportunities to gear up myself with the most sought-after Python skill in this programme. I have had an enjoyable study experience at PolyU and built a close rapport with AMA professors, staff and my fellow classmates. True Yip |  |
 | Data Analytic turns a massive amount of data into insightful and valuable information which benefit companies for future business development. The Data Science and Analytics programme has trained me with knowledge and analytical skills that greatly support my future career. Brian Ngai |
This programme combines mathematical knowledge with computer programming skill and emphasizes its application in various industries. Studying in AMA is enjoyable. In addition to the classroom study, AMA organizes a wide range of training and workshops to prepare us for future career development. I have made the most out of my study and well prepared for future challenges. Jeffrey Tsang |  |
 | As a student without solid mathematics background, it’s challenging for me to understand the advanced mathematics topics. AMA’s teachers are very supportive and patient. They guided me to fill the knowledge gap and develop passion in Mathematics study. In this inspiring and amicable learning environment, I was encouraged to delve deeper into statistics study. Currently, I am pursuing a postgraduate degree to further develop my applied statistics knowledge and hopefully contribute to the research development in future. Charlotte Ng |
BSc (Hons) in Investment Science was my first choice in JUPAS application. In addition to the statistics theories that I’m highly interested in, this programme also covers knowledge of other areas such as programming, economics and finance, and their application in solving real-life problems. Thanks to the opportunities offered by the Department, I have made the most of my 4 years at PolyU. From joining the Departmental Society of Applied Mathematics, going for an exchange in USA, to taking internship in Beijing, I seized all the chances to equip myself with professional knowledge, expand social circle and develop my interpersonal skill. Vincent Au |  |
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