Bachelor of Science (Honours) in Data Science and Analytics
數據科學及分析(榮譽)理學士學位


Sept 2019 Entry

Programme code: 63425

Duration and Credit Requirement


Mode of Study
Full-time
Normal Duration

2 years

Credits Required for Graduation

Normally 64 credits depending on the student's entry qualification
(plus 2 training credits of Work-Integrated Education)

Programme Intake
25
Fund Type
Government-Funded
Consider Second Choice Applications
Yes, but preference will be given to first choice applications.
Programme Leader(s)

Programme Leader

Dr Raymond Sze
BSc, MPhil, PhD

Deputy Programme Leader

Dr Jiang Binyan
BSc, PhD

Assistant Programme Leaders

Dr Leung Chun Sing
BSc, BEng, MPhil, PhD

Dr Allen Tai
BSc, MPhil, PhD

Remarks
  • The credit requirements of this programme are indicative only and subject to review.
  • The exact study duration and number of credits to be transferred will depend on the entry qualifications of individual AD/HD admittees.
  • To give recognition to outstanding non-JUPAS admittees, the Department sets up a one-off entrance scholarship for non-JUPAS applicants. Please find the details here.
  • Info Seminar

    • Date: 25 January 2019 (Friday)

    • Time: 6:30pm - 7:30pm

    • Venue: Room P116, PolyU

Aims and Characteristics

Programme Aims

The programme is concerned with turning large scale data into intelligence through the application of cutting-edge techniques in mathematics, statistics and computer science. The aim is to produce graduates with expertise that cuts across the core disciplines of mathematics, statistics and computer science.  The programme emphasises the critical arc that runs from data to information, information to knowledge, and knowledge to decision making.

 

 

Characteristics

Our articulation programme is focused on the acquisition of analytical skills based on mathematics, statistics and computing, and their application to the management and analysis of data, as well as to the discovery of lawfulness from very large data sets or systems, now generally referred to as Big Data. Upon successful completion of the programme, students should be able to manage massive datasets and help to make appropriate decisions in whatever careers they pursue.

Curriculum

Students must complete all of the Discipline-Specific Requirement (DSR) and General University Requirement (GUR) subjects to fulfil the credit requirement for graduation, except those who are given credit transfers due to their prior study.

 

(A) The DSR subjects comprise Core Subjects and Elective Subjects as listed below.

Core Subjects* (At least 16 subjects with total 49 credits)

  • Big Data Analytics
  • Business Intelligence and Customer Relationship Management
  • Capstone Project
  • Data Mining and Data Warehousing
  • Database Systems
  • Decision Analysis
  • English for Technical Project Writing
  • Forecasting and Applied Time Series Analysis
  • High Dimensional Data Analysis
  • Mathematical Methods for Data Science
  • Probability & Distribution
  • Professional Communication in Chinese for Data Science
  • Programming for Data Science
  • Simulation
  • Statistical Modeling for Discovery
  • Statistics for Data Science

* Zero-credit subjects - Admitted students with insufficient background in mathematics and/or programming are required to pass the zero-credit subject(s) Calculus and Linear Algebra, Principles of Programming or their equivalents.

 

Elective Subjects (At least 2 subjects with total 6 credits)

  • Applied Probability Models for Investment
  • Computational Methods
  • E-commerce Technology and Applications
  • Econometrics
  • Environmental Impact and Assessment
  • Financial Computations and Programming
  • Information Systems Audit and Control
  • Medical Informatics
  • Operations Research Method
  • Optimization Methods
  • Urban Planning (Workshops)
  • Web Application Design and Development

(B) GUR Subjects# (9 credits)

The GUR subjects comprise 6 credits of Cluster-Area Requirement (CAR) subjects and 3 credits of Service Learning (SL) subjects.

Extra credit bearing subject - Students not meeting the equivalent standard of the Undergraduate Degree Language Communication Requirements (LCR) based on their previous academic performance in AD/HD programmes will be required to take additional credits (English and/or Chinese) on top of the programme's normal credit requirement.

 

(C) Work-Integrated Education (2 training credits)

Students are required to spend a minimum of three weeks or 120 hours working in firms either during summer vacation or as part-timers. Discipline-related summer placements may be found in Hong Kong, the Chinese Mainland or overseas. These, and other forms of work experience, can be counted towards the WIE requirement, subject to the approval of the department.

 

Professional Examination

Upon the completion of programme, graduates are expected to receive partial exemption from the professional assessment of:

  • Hong Kong Statistical Society (HKSS)
  • Royal Statistical Society of UK (RSS)

Recognition and Prospects

Career Prospects

The BSc(Hons) in Data Science and Analytics programme is designed to develop students’ analytical, critical thinking, problem-solving and communication skills, which enables them to pursue a variety of careers in areas such as finance, telecoms, information technology, market research, manufacturing and pharmaceuticals. Graduates can also pursue further studies in postgraduate programmes locally or overseas.

Entrance Requirements

An Associate Degree or a Higher Diploma in IT, Statistics, Engineering, Science or Business from The Hong Kong Polytechnic University, or similar qualifications from other institutions or the equivalent.

 

Selection Criteria

Suitable applicants will be invited to interviews, which aim to evaluate the potential for and interest of applicants in the programme, and to test their communication skills and general knowledge relevant to the programme.

Enquiries

For further programme information, please contact:
The General Office (tel: 2766 6946/2766 6948; email: dsa.info@polyu.edu.hk)
Dr Raymond Sze (tel: 2766 5642; email: raymond.sze@polyu.edu.hk
)
Dr Jiang Binyan (tel: 2766 6349; email:  by.jiang@polyu.edu.hk)
Dr Leung Chun Sing (tel: 3400 3905; email: chun-sing-hkpu.leung@polyu.edu.hk)
Dr Allen Tai (tel: 2766 4694; email: allen.tai@polyu.edu.hk)

 

Student Message


As a finance graduate, I am well aware of the growing importance of data handling skills and the application of analytics software in the financial market. With a huge amount of data on hand, data scientist can conduct in-depth analyses to monitor every detail of the market. I believe that effective data handling skills can help in evaluating how successful an individual or a business is. Having observed this emerging trend that will dominate the business world, I changed my study field from business to data science. This new knowledge will also help me broaden my horizons beyond the business field. Big data have a very wide range of applications, such as astronomy and space science, environmental protection and civil planning, and medical science and financial market analysis. Data science graduates possessing analytics skill applicable in different industries can find countless opportunities.

 

This Data Science and Analytics programme combines mathematical study with computer programming and emphasizes its application in various industries. In this programme, I have acquired data analytics programming skills that I had no knowledge of before. The curriculum design is well-rounded and covers adequate computing courses, which helps students without computing backgrounds like me get up to speed in our studies in no time. My mathematical skills are also greatly enhanced. The study in AMA is enjoyable; both the teaching and administrative staff provided me with a lot of support throughout my university life. In addition to the classroom study, the Department organizes a wide range of training and workshops from time to time, to prepare us for our future career development. It also provides us with various kinds of opportunities. For example, I have secured a business analyst internship in a FORTUNE 500 company with the help of the department. I will also go on an exchange to one of the most prestigious universities in Singapore next semester. I will make the most of my study time in AMA and equip myself to face future challenges.

 

The demand for data scientists and analysts is growing. It takes courage to change to a new study field but I do not regret my decision.


Jeffrey Tsang



Additional Documents Required


Personal Statement

Required

Transcript / Certificate

Required


Interview Arrangement


Date: Between October 2018 and April 2019
Mode:Individual interview
Aims:

To evaluate the potential for and interest of applicants in the programme, and to test their communication skills and general knowledge relevant to the programme.

Medium:English
Duration:

About 15-30 minutes

Remark:

Applicants may be invited to interviews. No make-up interviews or earlier interviews will be arranged for applicants who fail to attend the scheduled interviews.