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


Sept 2020 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
BS, PhD

Assistant Programme Leaders

Dr Leung Chun Sing
BSc, BEng, MPhil, PhD

Dr Allen Tai
BSc, MPhil, PhD

Remarks
  • For more programme information, please visit http://www.polyu.edu.hk/ama/ug/63425/.
  • 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 stay tuned for details.

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
  • Forecasting and Applied Time Series Analysis
  • High Dimensional Data Analysis
  • Mathematical Methods for Data Science
  • Probability & Distribution
  • Professional Communication in Chinese for Data Science
  • Professional English for Data Science and Analytics Students
  • 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)

  • Algorithmic and High Frequency Trading
  • 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 Methods
  • Optimization Methods
  • Statistical Machine Learning
  • 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.

 

 

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.

 

Professional Recognition

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

  • Hong Kong Statistical Society
  • Royal Statistical Society of the UK 

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 local educational institutions or equivalent.

 

 

Enquiries

For further programme information, please contact:
The General Office (tel: 2766 6948; email: dsa.info@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



自中學畢業後,我便投身職場,任職媒體監察助理,為各大品牌提供市場調查服務。在這一年工作中,我明白到市場分析數據對這些品牌的重要,由此啟發我對市場學的興趣。考慮自身的能力後,我便修讀了理大專上學院的市場學副學士。市場學所涵蓋的範圍甚廣,而我最感興趣的是市場調查。恰巧在我修畢副學士課程後,理大應用數學系開辦兩年制的「數據科學及分析」銜接學士課程,於是我便毅然報讀。除了上課外,「數據科學及分析」課程還為我們提供其他不同的學習機會。在這兩年間,學系舉辦了多次的工作坊以助我們認識和應對行業的變化,並安排一些與學科相關的實習工作機會,協助我們獲取職場的工作經驗。每年暑假,學系還舉辦遊學團,讓我們擴闊眼界之餘,還了解到海外升學或就業的資訊。承蒙理大培育,本年七月中旬,我將於銀行任職客戶價值管理主任,擔任顧客分析工作。這工作需要運用到不少數據分析的專業技能,還涉及市場學中的客戶關係管理技巧,正好給予我一展所長的機會。


Cheryl Wong





Additional Documents Required


Personal Statement

Required

Transcript / Certificate

Required


Interview Arrangement


Date: Between November 2019 and April 2020
Mode:Individual interview via Skype
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 10-15 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.
  • The mode of interview has been updated.