MSc Data Science (NCR# 252794)/
Postgraduate Diploma in Data Science (NCR# 253137) /
Postgraduate Certificate in Data Science (NCR# 253138)

(NCR# 252794)

This Master’s Degree in Data Science course is designed for aspiring data science professionals in Hong Kong. This course prepares Hong Kong students with technical and practical skills to master big data analytics, a key to success in future business, digital media and science sectors. Dive deep into industry-specific topics, including data mining, machine learning, data analytics and data visualisation, along with data and cybersecurity.

Our close links to the industry and businesses, as well as the research expertise of our academics, makes this course unique. We strive to ensure that the course curriculum is developed to cater to the in-demand needs of employers in the data science field.

Graduates of the MSc Data Science course are recognised by OpenCertHub.com with papers exemption for the Certified Data Professional in Open-source Software (CDPOS™) Module 1: CDPOS-M01 “Big Data and Open Source Fundamentals Certification”.

CDPOS™ is designed for certifying Data Literacy for an employee in digital transformation enterprise, currently offering 3 types of Role-Based certification (Data Citizen, Citizen Data Scientist, and Advanced Citizen Data Scientist), which includes 4 types of module certification (CDPOS-M01 Big Data and Open Source Fundamentals, CDPOS-M02 Data Visualisation Essentials, CDPOS-M03 Data Analytics Essentials and CDPOS-M04 Python for Big Data Analytics). Please click here for more course details.

Programme features:

A course based in Hong Kong on applying data analytics for forecasting and insights
Education to transform individuals into Data Scientists
Introduction and advanced learning of R Language and Python
The harnessing of new forms of data with evolving computing skills
Completion of 180 credits with 4 modules and 1 master’s project in 21 months
Assessment methods include written reports and research papers, hands-on assignments, and a master’s project
Studying in Hong Kong campus with local academic and student support teams
An easy-to-use interactive online learning platform with access to more than 10,000 online learning resources, including e-books and business journals
Upon successful completion of their data science studies in Hong Kong, students will be awarded the same certificate and qualifications as university students in the UK.
Graduates are entitled to an additional certification from OpenCertHub – CDPOS-M01 “Big Data and Open-source Fundamentals Certification”. A collaborative scholarship is available for CDPOS certificate holders. For more details, please click here.

Content

180 credits 4 modules and 1 Project

Postgraduate Certificate in Data Science stage:
CETM50 - Technology Management For Organisations (30 credits)

Learning Outcomes:

Have Critical appreciation of the policies and procedures to manage data and information securely, to manage risk in technology management.
Critically analyse the strategic challenges, risks, opportunities and practical applications afforded by cybersecurity and data science for organisations to enable effective business operation and ensure business continuity.
Critically assess the appropriate technologies, infrastructures, tools and techniques required to address practical problems and challenges for organisations in data science and cybersecurity.
Complete analysis and evaluation of the professional, legal and ethical requirements of secure big data management in business and industrial environments.

CETM24 - Data Science Fundamentals (30 credits)

Learning Outcomes:

Demonstrate a deep understanding of data science problems and hence raise awareness of the broad range of tasks/skills required to be a data scientist.
Understand the broad types of data (including temporal and spatial), variables to suitably employ in the range of techniques for data transformation, fusion and analysis and data presentation and visualisation.
Have deep understanding of the Data Science lifecycle (collect, clean, analyse, share, act) and a related broad understanding data science platforms (e.g. Hadoop, Spark) and data science programming languages (e.g., R, Python).
Select and apply key analytical techniques (e.g. traditional and intelligent analytics) in order to be able to conduct a big data analysis across the whole data science lifecycle on modern data science platforms and with data science programming languages.
Conduct pre-processing, data fusion and data analysis on a wide variety of data sets and to report the results.
Visualise, present and organise data in a variety of formats.

Postgraduate Diploma in Data Science stage:
CETM46 - Data Science Product Development (30 credits)

Learning Outcomes:

Developed critical understanding of the use of data repositories for storage of data sets for decision making in organisations.
Utilisation of the state of art of data science methodologies and software tools for data analysis applications development.
Developed critical understanding of modern data science systems and their ecosphere.
Conduct critical analysis, selection and evaluation of data science methodologies and software tools onto a broad range of datasets and data analysis applications.
Design and develop data science systems using various data repositories and data models.
Develop data science products with modern data systems, visualisation technologies, software tools and their ecosphere.

CETM47 - Machine Learning and Data Analytics (30 credits)

Learning Outcomes:

Developed a critical understanding of trends, tools, and current developments in the areas of Machine Learning, Data Mining and Data Analytics.
Developed a critical understanding of Machine Learning, Data Mining and Data Analytics tools.
Developed understanding of the professional, ethical, social and legal considerations involved in Data Mining and Data Analytics.
Critically assess, choose and apply the appropriate Machine Learning, Data Mining and Data Analytics formalisms and tools to practical problem.
Identify and assess data for the use of Data Mining and Data Analytics tools.
Define, explain and interpret the results obtained from the practical application of Machine Learning, Data Mining and Data Analytics tools.

MSc Data Science stage:
PROM02 - Computing Master's Project (60 credits)

Learning Outcomes:

Have a critical appreciation of the nature of research including ethical approaches and the goals of academic reading, information searching and communication.
Have a critical appreciation of the clarity, scientific approach and structure of academic writing.
Have an understanding and critical awareness of project management concepts, techniques and tools for the management of projects.
Have Advanced knowledge in a specialised area of the relevant discipline.
Critically assess the ethical, legal and professional issues in research relevant to your programme of study when planning research.
Independently design and undertake a major project on a topic which relates to the forefront of the academic area under study.
Reflect objectively on method, process and outcome of the project.
Independently critique relevant current literature, conduct empirical research or advanced technical or professional activity, in the area under study demonstrating self-direction and originality in tackling and solving problems or conceptualising solutions.
Deal with complex issues in the area of study both systematically and creatively making informed judgements in the absence of complete data.

Mode of Study

Part Time Face-to-face tutorials

This master’s programme of Data Science can be completed in 21 months.
Each module consists of 60-72 hours of face-to-face tutorials.

Assessment

4 assignments and 1 project Four in total

There is one assessment for each module (Four in total).
There is one project for this programme.

Learning Aid

Hong Kong based Academic & Student Support Teams

Access to an online study platform where all study materials and student handbooks are available and accessible
A dedicated tutor for academic support who you can contact for any academic queries
Access to the Student Support Team for administrative support
An induction day before attending tutorials

Entry Requirements

Degree / relevant work experience

A bachelor’s degree with honours (2:2 or above / lower second class level) in computing or related non-computing discipline (i.e. mathematics, statistics, engineering); OR
A bachelor’s degree with honours (2:1 or above / upper second class level) in relevant non-computing discipline (i.e. degree with numeracy included and/or application of big data as a significant theme); OR
Applicants with five years of relevant business or industry experience; AND
English proficiency is equivalent to HKDSE Level 3 / IELTS 6.0. Candidates whose first language is English or whose previous verified qualification was taught and assessed in English are exempted from the aforementioned English Language requirement.

Tuition Fee

3 instalments

Postgraduate Certificate Stage: HKD45,000* / 6 months
Postgraduate Diploma Stage: HKD45,000* / 6 months
MSc Data Science Stage: HKD45,000* / 9 months

*This does not include the HKD600 administration fee. The tuition fees shown above refer to the fees for 2023/24, and the fees for 2024/25 are subject to review.

Funding

Scholarship

Enrol to enjoy up to HKD5,000 Bursary!^

^Terms and conditions may apply. For further information please contact us by phone (852) 2992 0133 or by email ([email protected])

How To Apply

4 intakes per year October, January, April and July

Please click here to Apply, our Recruitment Advisor will assist you shortly.

Graduate Sharing

Student name: Terry Lau Siu Hong
Year of graduation: 2023
Programme of study: MSc Data Science

Sharing: I was overwhelmed with a sense of pride and accomplishment to find out that I had won the academic excellence award. It was truly an honour to be recognised for my achievements.

I chose the University of Sunderland in Hong Kong because of its reputation for academic excellence and its internationally recognised data science programme. What I liked most about my study at Sunderland HK was the supportive learning environment. The lectures and programmes were well-designed and engaging, and the staff were always available to provide guidance and support.

With the skills and knowledge I gained in big data, machine learning and artificial intelligence, I can better develop data-driven strategies for my company. The education I received at the university has been instrumental in helping me to achieve my career goals.

Information is accurate at the time of publication and is subject to change. The programmes above are registered at the Non-local Courses Registry (NCR). It is a matter of discretion for individual employers to recognise any qualification to which this course may lead.

Any queries and complaints suspected to have contravened any Law of the People’s Republic of China on Safeguarding National Security in the Hong Kong Special Administrative Region (“National Security Law”) or to be contrary to the interest of national security, please report to our registrar, Mr. Hector Rivera [email protected]

Application Deadline:30/12/2024
Duration:6 months (Postgraduate Certificate stage) + 6 months (Postgraduate Diploma stage) + 9 months (MSc stage)
Study Level:Postgraduate Cert to Master
Discipline:Data Science, Master Degree

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MSc Data Science (NCR# 252794)/
Postgraduate Diploma in Data Science (NCR# 253137) /
Postgraduate Certificate in Data Science (NCR# 253138)

180 credits 4 modules and 1 Project

Part Time Face-to-face tutorials

4 assignments and 1 project Four in total

Hong Kong based Academic & Student Support Teams

Degree / relevant work experience

3 instalments

Scholarship

4 intakes per year October, January, April and July

Graduate Sharing

Programme Information

Get more details from our Admissions Advisor now.

Get in touch with us

Request Information

MSc Data Science (NCR# 252794)/ Postgraduate Diploma in Data Science (NCR# 253137) / Postgraduate Certificate in Data Science (NCR# 253138)

180 credits 4 modules and 1 Project

Part Time Face-to-face tutorials

4 assignments and 1 project Four in total

Hong Kong based Academic & Student Support Teams

Degree / relevant work experience

3 instalments

Scholarship

4 intakes per year October, January, April and July

Graduate Sharing

Programme Information

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