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What will I learn?

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 2 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.

Core Areas of Study

6 Compulsory Subjects (18 credits)

  • Advanced High Dimensional Data Analysis
  • Big Data Computing
  • Data Structures and Database Systems
  • Deep Learning
  • Optimization 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
  • Dissertation
  • Forecasting and Applied Time Series Analysis
  • Graphs and Networks
  • Investment Science
  • Loss Models and Risk Analysis
  • Mathematical Modeling for Science and Technology
  • Multi‐criteria Optimization
  • Operations Research Methods
  • Optimal Control with Management Science Applications
  • Probability and Stochastic Models
  • Scientific Computing
  • Simulation and Risk Analysis
  • Statistical Data Mining
  • Statistical Inference

Study options

Full Time (1.5 years)

Tuition fees
HK $8,800 Per Credit
Application deadline

Expected April 2023

More details

Start date

Expected September 2022

Venue

Faculty of Applied Science and Textiles, The Hong Kong Polytechnic University

The Hong Kong Polytechnic University,

Room TU502 Yip Kit Chuen Building,

Kowloon City, Hong Kong, Kowloon

Entry requirements

For students from United States

To register for the degree of MPhil, a student shall hold: A Bachelor’s degree with first or second class honours of The Hong Kong Polytechnic University or a recognized university; or other academic qualifications which are deemed to be equivalent. PolyU may accept other equivalent qualifications. The decision is made on an individual basis. The requirements for those who do not have a degree for which English was the language of instruction at a recognized university are: An overall score of at least 6.5 (with score for the writing component at 6.0 or above) in the International English Language Testing System (IELTS); OR A Test of English as a Foreign Language (TOEFL) score of 80 or above for the Internet-based test (with a writing score of 23 or above) or 550 or above for the paper-based test (with a score of 4 or above in the Test of Written English). Alternatively, consideration will be given to acceptable scores in other internationally recognized public examinations, such as the Graduate Record Examination (GRE) or the Graduate Management Admission Test (GMAT). All English language test scores are considered valid for five years after the date of the test.

For international students

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.

For applicants who are not native English speakers and whose first degree qualifications are not obtained through the English medium, they are required to obtain one of the following to ensure that our admittees have reached a compatible English language standard:

A Test of English as a Foreign Language (TOEFL) score of 80 for the Internet-based test or 550 for the paper-based test; OR

An overall Band Score of at least 6 in the International English Language Testing System (IELTS).

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