A Data Science Programme is essential due to the increasing reliance on data in today's world. Organizations across industries are recognizing the value of data-driven decision-making and the potential for extracting valuable insights from vast amounts of data.

Combination of fundamental principles and practical applications

The Master of Science in Data Science (MScDS) is designed in a multidisciplinary way, which covers the frontiers of data science knowledge on topics of emerging technologies such as (generative) artificial intelligence and multimedia technologies (text, images, etc.).

Foundation for future career/academic planning

Students must complete seven required courses and three elective courses and earn a total of 30 credits to graduate. The required courses equip students with the skills needed to work with large data sets and utilize emerging technologies. The diverse elective courses meet students' interests, abilities, and career plans, while allowing students to learn more advanced and practical knowledge in a variety of fields.

Features of the programme

• Integrate different disciplines to allow students to know all the important aspects of data science and how it is used in the real world. It trains professionals to analyse data with data science tools and convert it into useful information.
• Combine knowledge of artificial intelligence, data science with different real-word analytics including blockchain, marketing, healthcare, geographical information system, etc.
• It is ideal for professionals, decision and policy makers who need to process and analyse big data, as well as healthcare and public utility sector practitioners who understand the importance data science and artificial intelligence in enhancing the quality of society and effectiveness of operations.
• Develop students' analytical skills, critical thinking, and problem-solving abilities to enable graduates to pursue careers as business analysts, data analysts, data scientists, and artificial intelligence experts/consultants in a variety of industries.

Mode of Study

Full-time

Programme Duration

Medium of Instruction

English

Credits Required

30 credits

Modules Required

7 core courses (21 credits), 3 elective courses (9 credits)

Programme Curriculum

Core courses (7 courses, a total of 21 credits):

1. CDS532 Programming for Data Science (3 credits)
2. CDS533 Statistics for Data Science (3 credits)
3. CDS534 Database Management (3 credits)
4. CDS535 Data Mining (3 credits)
5. CDS536 Data Science Project (3 credits)
6. CDS521 Foundation of Artificial Intelligence (3 credits)
7. CDS524 Machine Learning for Business (3 credits)

Elective courses (any 3 courses):

1. CDS537 Introduction to Cyber Security (3 credits)
2. CDS538 Cloud Computing (3 credits)
3. CDS539 Natural Language Processing (3 credits)
4. CDS540 Computer Vision (3 credits)
5. CDS541 Operations Management (3 credits)
6. CDS542 Data Visualization (3 credits)
7. CDS543 Social Computing (3 credits)
8. CDS544 Mobile Edge Computing (3 credits)
9. CDS515 Business Decision Making with Software (3 credits)
10. CDS525 Practical Application of Deep Learning (3 credits)
11. CDS527 Big Data Analytics (3 credits)
12. CDS528 Blockchain (3 credits)
13. CDS530 Healthcare Analytics (3 credits)
14. SCI501 Geospatial Intelligence for Sustainable Development (3 credits)

Pre-entry Course

Applicants with no or limited background in computer science or statistics will be required to complete the corresponding pre-entry courses below:

• Introduction to Computing
• Statistic

Graduation Requirements

To qualify for the award of the Master of Science in Data Science offered by Lingnan University (LU), students must, where applicable:

• Complete 10 courses (7 core courses, 3 elective courses) and obtain a minimum of 30 credits;
• Achieve a minimum CGPA of 2.67;
• Fulfil the University exit requirement on English language competency, if applicable; and fulfil all University/programme requirements.
• A student who fulfils all the requirements for graduation shall be awarded a Master of Science in Data Science degree with one of the following classifications:

Students will be awarded a Postgraduate Diploma in Data Science if they complete no less than four courses equal to 12 credits with a minimum Cumulative GPA of 2.30. Acceptance of an intermediate award implies an intention not to complete the final award.

Last Updated: 27 March 2024

Tuition Fees

Application Fee

HKD 400

Financial Assistance

Government Student Financial Assistance

Local students are eligible for applying the Extended Non-means Tested Loan Scheme (ENLS). For eligibility and details, please visit the Working Family and Student Financial Assistance Agency's website

Scholarships

Scholarships might be considered for outstanding students on the basis of academic merit. All students admitted to the programme will automatically be the candidates for the scholarships.

Last Updated: 24 January 2024

Admission Requirements

Applicants shall fulfill the minimum admission requirements for taught master’s degree programmes as follows and additional admission requirements set by the programme.

Minimum Admission Requirements

Academic Qualification(s)

• hold a relevant bachelor’s degree awarded by a tertiary education institution recognised for this purpose by the University; or
• have obtained an equivalent qualification; or
• have provided satisfactory evidence of academic and professional attainment.

English Proficiency

In addition to the above, applicants whose degree or, exceptionally, an alternative qualification deemed equivalent from a tertiary institution is not using English as the medium of instruction (MOI) for the programme should obtain:

• a minimum score of 550 (paper-based test) or 79 (internet-based test) in the Test of English as a Foreign Language (TOEFL)^{1 2}; or
• a band score of 6.5 or above in the International English Language Testing System (IELTS)¹, or
• an equivalent score in a recognised test, or
• an equivalent qualification to prove his/her English language proficiency which will be considered on a case-by-case basis.

¹For IELTS and TOEFL qualifications, the University only accepts results that are within the validity period, viz. 2 years, from the time of submission of an admission application for the specific intake cohort.

²For an applicant using TOEFL “MyBest scores” to fulfill the minimum required score of 79, the programme should use interview or other means to assess the applicant’s proficiency in English.

Additional Admission Requirements

• Applicants with no or limited background in data science and computing will be required to complete and pass pre-entry courses prior to the start of the programme.

Please refer to the programme website for details.

Application Method

Apply through the online application system:

https://www.ln.edu.hk/admission/apply

Last Updated: 24 January 2024