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
For more Scheme information, please visit www.polyu.edu.hk/ama/ug
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 and 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 optimisation 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 Department, no later than the commencement of the second year of study to be admitted to the Secondary Major.
Credit Requirement
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 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 international applicants.
Other Information
For further programme information, please contact
the General Office (tel.: 2766 6946; email: ds.info@polyu.edu.hk).
This programme consolidated my understanding of basic mathematical theories and algorithms. I also learned about statistical and financial models. The content of the computing modules enabled me to work more effectively on data handling, which is especially important in this age of big data. AMA’s staff are friendly and approachable, welcoming students to express their opinions on the curriculum design of the programme. They encourage students to join workshops and training courses offered by the Department, such as Advanced Excel or Python, and through opportunities for practical application, students get to know how real-life situations can be explained by or deviate from known models, thus developing critical thinking skills. Exchanges and internship opportunities are always open for students to strengthen their learning experience and help them identify their future paths. Heidi Wan |  |
 | AMA offers a diverse learning opportunities, including computer programming workshops and internships. This programme has equipped me with data analytic skills which greatly support my current job as a Customer Value Management Officer in bank. Cheryl Wong |
I am grateful for the opportunities I had to equip myself with the most sought-after Python skills taught 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 analytics turns a massive amount of data into insightful and valuable information that benefits companies for future business development. The Data Science and Analytics programme provided me with knowledge and analytical skills that greatly support my career. Brian Ngai |
This programme combines mathematical knowledge with computer programming and emphasises its application in various industries. AMA organises a wide range of training opportunities and workshops to prepare students for their future career development. I have made the most out of my study at AMA and feel well prepared for future challenges. Jeffrey Tsang |  |
 | As a student who started without a solid mathematics background, it was a challenge for me to understand the advanced topics of the programme. But AMA’s teachers are very supportive and patient. They helped me fill my knowledge gaps and develop a passion for mathematics. In this inspiring and amicable learning environment, I was encouraged to delve deeper into the study of statistics. Currently, I am pursuing a postgraduate degree to develop my applied statistics knowledge and hopefully contribute to research development in the future. Charlotte Ng |
The BSc (Hons) in Investment Science was my first choice in my JUPAS application. In addition to the statistics theories, where my main interest lies, 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 and going on an exchange to the USA to taking an internship in Beijing, I have seized all the chances offered to equip myself with professional knowledge, expand my social circle and develop my interpersonal skills. Vincent Au |  |
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