What will I learn?

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

Which department am I in?

Faculty of Science

Study options

Full Time (1.5 years)

Tuition fees

HK$206,000.00 (21,85,584) per year

HK $10,300 per credit

*Price shown is for indicative purposes, please check with institution

Start date

Expected September 2023

Venue

The Hong Kong Polytechnic University

ST305, 3/F, Ng Wing Hong Building,

Hung Hom,

Kowloon City, Hong Kong, Kowloon

Entry requirements

For students from United States

Applicants must have a Bachelor's degree from an institution that is recognized by PolyU. In addition, you must meet the entrance requirements that are specified by individual programmes. PolyU may accept equivalent qualifications. The decision is made on an individual basis. 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).

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.

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 following minimum English language requirement for admission purpose, unless otherwise specified by individual programmes concerned:

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).

*There may be different IELTS requirements depending on your chosen course.