Postgraduate Programs 2022/23
Master of Science Program in Big Data Technology
Award Title

Master of Science in Big Data Technology

Program Short Name

MSc(BDT)

Mode of Study

Both full- and part-time

Normative Program Duration

Full-time : 1 year
Part-time : 2 years

Program Fee

Full-time: HK$210,000
Part-time: HK$180,000

New students admitted with credit transfer are also required to pay the full program fee. Students who take additional courses or need to retake any courses are required to pay additional fee.

Program Advisor

Program Director:
Prof Ke YI, Professor of Computer Science and Engineering

Big data is poised to change the way enterprises function and a society operates, and is changing the way engineering and science is conducted. The Master of Science (MSc) Program in Big Data Technology aims to educate students about big data and issues related to big data. Students are expected to be familiar with the workflow of big data systems and social and societal implications of big data systems. Jointly offered by the Department of Computer Science and Engineering and the Department of Mathematics, the program integrates different disciplines to allow students to know all the important aspects of big data and how it is used in the real world.

On successful completion of the program, graduates will be able to:

  1. Identify, explain, and use Big Data infrastructure;
  2. Solve Big Data integration and storage problems;
  3. Perform various data analytic tasks using Big Data management and computing techniques;
  4. Derive knowledge and strategies from Big Data analytics and apply them to privacy protection and policy making; and
  5. Investigate existing problems on Big Data and conduct original Big Data research.
  1. Minimum Credit Requirement

    30 credits 
     

  2. Credit Transfer  

    Subject to the approval of the Program Director and the University regulations governing credit transfer, a maximum of 9 credits can be transferred to the program.
     

  3. Core Courses

    12 credits
     

MSBD 5001
MSBD 5002
MSBD 5003
MSBD 5004

 

  1. Elective Courses

    18 credits
     

MSBD 5005
MSBD 5006
MSBD 5007
MSBD 5008
MSBD 5009
MSBD 5010
MSBD 5011
MSBD 5012
MSBD 5013
MSBD 5014
MSBD 5015
MSBD 5016
MSBD 5017
MSBD 5018
MSBD 5019
MSBD 6000

 

  1. Remarks

  • Subject to the approval of the Program Director, students may take a maximum of 6 credits of CSIT courses from the MSc Program in Information Technology as partial fulfillment of the graduation requirements of the program.

  • Part-time students may take a maximum of 9 credits in each term.

  • Students failing to meet the graduation grade average (GGA) requirement of 2.850 or above are required to repeat or take additional course(s) even if they attain passing grades for all courses.
     

Last update: 10 May 2022

To qualify for admission, applicants must meet all of the following requirements. Admission is selective and meeting these minimum requirements does not guarantee admission.
 

1. General Admission Requirements of the University
  • Applicants seeking admission to a master's degree program should have obtained a bachelor’s degree from a recognized institution, or an approved equivalent qualification.

2. English Language Admission Requirements

Applicants have to fulfill English Language requirements with one of the following proficiency attainments:

  • TOEFL-iBT: 80*

  • TOEFL-pBT: 550

  • TOEFL-Revised paper-delivered test: 60 (total scores for Reading, Listening and Writing sections)

  • IELTS (Academic Module): Overall score: 6.5 and All sub-score: 5.5

* refers to the total score in one single attempt


Applicants are not required to present TOEFL or IELTS score if

  • their first language is English, or

  • they obtained the bachelor's degree (or equivalent) from an institution where the medium of instruction was English.

3. Program-Specific Admission Requirements
  • A bachelor's degree in Computer Engineering, Computer Science, Mathematics or a related area, or

  • (i) A bachelor’s degree in other disciplines and (ii) relevant work experience in IT and Mathematics related fields