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Master of Science in Data Science and Analytics
數據科學及分析理學碩士學位

Sept 2022 Entry
Programme code: 63027

Faculty of Applied Science and Textiles
Department of Applied Mathematics

Stream Code

DFM (Full-time)
DPM (Part-time)

Mode of Study Mixed Mode

Normal Duration

1.5 years (Full-time)
3 years (Part-time)

Credits Required for Graduation

30

Initial Registration Credits

3 for local students
9 for non-local students
 

Fund Type Self-Financed

Tuition Fee

HK$9,800 per credit for local and non-local students

Programme Leader(s)

Programme Leader
Dr Jiang Binyan
BS, PhD

Deputy Programme Leader
Dr Zhang Zaikun
BSc, PhD

Assistant Programme Leader
Dr Li Ting
BS, MPhil, PhD

Remarks

Non-local applicants must be registered as full-time students.

Aims & Characteristics

Programme Aims

In today's era of big data, large data sets are generated every day in various areas of society and industry, such as the Internet, social networking and finance. It is a challenging task to analyse and extract information from this unprecedentedly large volume of data. To create value from such data, one must combine techniques from mathematics, statistics and computer science. This programme nurtures graduates with expertise that cuts across the core disciplines of mathematics, statistics and computer science. It develops students’ analytical and critical thinking, as well as their problem-solving skills. This enables graduates to pursue careers as data analysts in various industries, such as finance and information technology.

 

Characteristics

Data Science and Analytics involves the use of mathematical, statistical and computing techniques to extract useful information from large-scale data and make decisions accordingly. Statistics, optimisation methods and computer science are widely acknowledged to form the three pillars of modern data science. This programme is designed to provide a balanced treatment of these three pillars, with the aim of cultivating future data analysts.

 

Graduates who have highly developed mathematical, statistical and computing skills are thus in great demand globally, in both industry and research.

Curriculum

Programme Structure

Students studying for the MSc* award must complete:
Option 1: 6 Compulsory Subjects (18 credits) and 4 Elective Subjects (12 credits); OR
Option 2: 6 Compulsory Subjects (18 credits), 1 Elective Subject (3 credits) and a Dissertation (9 credits)

 

Students who opt for the Dissertation should have completed 6 Compulsory Subjects with good academic results. Normally, only students who have completed 6 Compulsory Subjects (18 credits) with a GPA of 3.0 or above at the end of Semester Two of first year will be considered for Option 2.

 

* Students who do not complete the programme but have passed 6 Compulsory Subjects (18 credits) and 1 Elective (3 credits) will be awarded a Postgraduate Diploma.

 

For details of the programme structure, please refer to https://www.polyu.edu.hk/ama/pg/63027/overview/.

 

Core Areas of Study

6 Compulsory Subjects (18 credits)

  • Advanced High Dimensional Data Analysis
  • Big Data Computing
  • Data Structures and Database Systems
  • Deep Learning
  • Optimisation Methods
  • Principles of Data Science


Elective Subjects (Each subject carries 3 credits)

  • Advanced Data Analytics
  • Advanced Operations Research Methods
  • Advanced Topics in High Frequency Trading
  • Applied Linear Models
  • Artificial Intelligence Concepts
  • Decision Analysis
  • Forecasting and Applied Time Series Analysis
  • Graphs and Networks
  • Investment Science
  • Loss Models and Risk Analysis
  • Mathematical Modelling for Science and Technology
  • Multi‐criteria Optimisation
  • Operations Research Methods
  • Optimal Control with Management Science Applications
  • Probability and Stochastic Models
  • Scientific Computing
  • Simulation and Risk Analysis
  • Statistical Data Mining
  • Statistical Inference


Information on the subjects offered can be obtained at https://www.polyu.edu.hk/ama/pg/63027/curriculum/.

Entrance Requirements

  • A Bachelor's degree with Honours in mathematics, statistics, computer science, IT, engineering, science, or equivalent. Applicants with a Bachelor’s degree in another discipline and an adequate background in mathematics or IT will also be considered.


If you are not a native speaker of English, and your Bachelor's degree or equivalent qualification is awarded by institutions where the medium of instruction is not English, you are expected to fulfil the University’s minimum English language requirement for admission purpose. Please refer to the "Admission Requirements" section for details.

Other Information

Some of the subjects in this programme have been included in the Continuing Education Fund (CEF) list of reimbursable subjects (for course commencement before September 2024).

 

The CEF list includes:

  • Advanced High Dimensional Data Analysis
  • Deep Learning
  • Optimisation Methods
  • Principles of Data Science

Enquiries

For further information, please contact:
Prof. Zhao Xingqiu, Programme Leader
(tel: (852) 2766 6921; email: xingqiu.zhao@polyu.edu.hk);
or Dr Jiang Binyan, Deputy Programme Leader
(tel: (852) 2766 6349; email: by.jiang@polyu.edu.hk);
or Dr Zhang Zaikun, Assistant Programme Leader
(tel: (852) 2766 4592; email: zaikun.zhang@polyu.edu.hk);
or Miss Moon Wai Yan (tel: (852) 3400 3138; email: wai-yan.moon@polyu.edu.hk).

Programme Leaflet

Please click here to download.