Bachelor of Science with Honours in Data Science and Artificial Intelligence

School of Science and Technology Computing   Programmes   Full-time Programmes   Bachelor of Science with Honours in Data Science and Artificial Intelligence  

Bachelor of Science with Honours in Data Science & Artificial Intelligence

數據科學及人工智能榮譽理學士
Face-to-Face Full-time SSSDP JSSU70 BSCHDSAIJS
  • Overview
  • Curriculum
  • Study Plan
  • Admission

Introduction

The Bachelor of Science with Honours in Data Science and Artificial Intelligence programme (BSCHDSAIJS/JUPAS JSSU70) aims to provide graduates with the breadth of an advanced understanding of theories and practices in the field of Data Science and Artificial Intelligence.

BSc (Hons) in Data Science & Artificial Intelligence is the 5th curriculum update of the “BSc (Hons) in Statistical Analysis” program which is launched in 2012. The School of S&T has a good practice of regular inspection of the program curriculum to ensure the offered programs meet the market needs. It is no doubt that effective and efficient usage of data in the digital world nowadays can help to foster a better world/society.

However, people who are competent in harvest useful insights from a vast amount of data require a particular set of skills which is different from those offered by traditional academic program curriculums.

To ensure our students to acquire appropriate skills, regular meetings with various parties are arranged. The curriculum of HKMU BSc(Hons) in Data Science & Artificial Intelligence is resulted from the recommendations given by industry professionals, academic professors and employers in business sectors.

To meet the employers’ expectations, our curriculum incorporates SAS Institute official training materials and therefore students can take the Industrial certification (e.g. SAS programmer & SAS predictive modeler) examinations right after the completion of the respective courses.

Furthermore, students in this program are encouraged to expand their horizons via international organizations such as The Royal Statistical Society (RSS), The Institute for Operations Research and the Management Sciences (INFORMS), British Computer Society (BCS), Institute of Electrical & Electronics Engineers (IEEE).

Bachelor of Science with Honours in Data Science & Artificial Intelligence (BSCHDSAIJS) 數據科學及人工智能榮譽理學士 has acquired the following external recognitions:

  • SAS Joint University certification – SAS programming and Data Mining
  • The Hong Kong Council for Accreditation of Academic and Vocational Qualifications (HKCAAVQ) – Level 5

This programme provides multiple entry points: Year 1 Entry through JUPAS and Senior Year Entry through Direct Application at the HKMU website.

Entry PointsApplication MethodsCode
Year 1 EntryJUPAS / Direct Application #JSSU70 / BSCHDSAIJ1 #
Senior Year EntryDirect ApplicationBSCHDSAIJS

#Students who are not sitting the HKDSE this year and have an equivalent qualification such as IB or GCE-A Level should apply through [Direct Application].

More and more information are available in the digital society nowadays and new generations should be able to comprehend and utilize them to solve practical problems. Our curriculum does not focus on teaching ‘abstract’ theories but emphasizing in enabling the student’s capability to deliver a complete package of solution to practical problems.

Data science and AI are interdisciplinary as they draw on various disciplines, such as Mathematics, Statistics and Computer Science. Machine Learning is the core of data science and AI. It employs computer algorithms to interpret data and learn from the results for decision making and forecasting. Data science and AI can push forward business development, optimize business and operations, and create more attractive operating models. Data sources may come from tables, relational databases, texts, videos, audios, images, etc. Data scientists / AI specialists use data science methods, deep learning, machine learning and AI to discover clients, products, services, operations and market insights.

Intended Learning Outcomes

Graduates will be ready for entry-level roles of data scientists, AI specialist, data engineers, and data analysts in commercial firms and public institutions. To achieve this goal, the program aims to equip our graduates with four main competitive edges.

  • Domain knowledge (e.g. Underlying rationale to determine personal expenditure pattern; Decision-making of an economy as a whole; Concerns in mobile computing, information security and network security)
    • Microeconomics & Macroeconomics
    • Information security
    • Mobile computing
    • Network security
  • Adequate hand-on IT skills for solution developments
    • Visualization: Microsoft Power BI, Google Data Studio, Excel
    • Programming: SAS, Python, R
    • Machine Learning/Artificial Intelligence: SAS Enterprise Miner, Keras (deep neural network), RapidMiner
    • Database: Oracle, MangoDB, SQL, noSQL
    • Distributed system: cloud computing
  • Statistics and Analytics knowledge
    • Probability and Expectation
    • Hypothesis Testing
    • Time Series Analysis and Forecasting
    • Regression Analysis
  • Effective presentation skills (Writing/Speaking/Visualization)
    • Tailored English writing and presentation skills
    • Effective use of visualization tools
Student Achievements

HKMU Computing Graduates regularly show their strength in problem solving and academic paper writing in inter-varsity contests and competitions. Since 2010, they have won over 30 prizes and awards, affirming their competitiveness among the UGC universities.

Please refer to the Student Achievements or Best Projects page for more details.

Career Prospects

Data scientist is ranked number 1 in the United States (LinkedIn’s Most Promising Jobs of 2019), whereas AI specialist is ranked number 1 among the top 10 roles in the United States (LinkedIn’s 2020 Emerging Jobs Report).

Hong Kong has been lagging behind the US and the UK in the size of the data science and AI job market, but now the demand is very strong as typically hundreds of job vacancies are available at any one time. While many data science/AI jobs are operating in the business context, there are still a wide range of roles and job titles, reflecting the multi-talented nature of the area.

Graduates will be ready for entry-level roles of data scientists, AI specialists, data engineers, and data analysts in commercial firms and public institutions.

Further Studies

Graduates of this programme have been admitted to various postgraduate programmes in local and overseas universities. Graduates may choose to study for a postgraduate degree in an advanced area in Data Science or Artificial Intelligence or in other areas for the broadening of their exposure and skill set. Even pursuing for a doctoral research degree.


Enquiries

Dr. Tony Chan

Tel: 2768 6867

Email: tmtchan@hkmu.edu.hk

Programme Structure

The 4-year programme consists of a balanced set of subject-area courses, language courses, and general education courses.

CategoriesWeightings
 Core Courses120 Credits
 Elective Courses10 Credits
 General Education Courses20 Credits
 English Language Enhancement courses10 Credits
Total160 Credits
  • Core Courses: Provide training in some of the major pillars in modern computing and statistic: processing of information, networking of information, and management of information.
    • The core courses include programming, software development, software engineering, computing infrastructure, and databases.
  • Elective and Project Courses: Expose students to specialized topics related to Data Science and Artificial Intelligence.
    • The final year project courses provide an opportunity to develop in-depth knowledge and high-level thinking process in a research and development project on Data Science.
  • Other Activities: In addition to the development of technical knowledge and skills, students are expected to develop their soft skills such as teamwork and communication.
    • Students are encouraged to participate in various contests, seminars, and workshops for sharpening their competitiveness.
Core Courses
CodeTitleCredits
 COMP S202FJava Programming Fundamentals5
 COMP S203FIntermediate Java Programming and User Interface Design5
 COMP S208FIntroduction to Computer Programming5
 COMP S209FData Structures, Algorithms, and Problem Solving5
 COMP S264FDiscrete Mathematics5
 COMP S320FDatabase Management5
 COMP S321FAdvanced Database and Data Warehousing5
 COMP S333FArtificial Intelligence Algorithms5
 COMP S350FSoftware Engineering5
 COMP S351FSoftware Project Management5
 COMP S381FServer-side Technologies and Cloud Computing5
 COMP S382FData Mining and Analytics5
 COMP S460FAdvanced Topics in Data Mining5
 COMP S461FData Science Project10
 COMP S492FArtificial Intelligence5
 COMP S493FDeep Learning5
 MATH S141FAlgebra and Calculus5
 STAT S151FProbability and Distributions5
 STAT S251FStatistical Data Analysis5
 STAT S261FData Analytics with Applications5
 STAT S263FBig Data in Organizations5
 STAT S311FTime Series Analysis and Forecasting5
 STAT S366FSAS Programming5
Total:120 Credits

Elective Courses
CodeTitleCredits
 COMP S413FApplication Design and Development For Mobile Devices5
 ELEC S425FComputer and Network Security5
Total:10 Credits

General Education, English Language
CodeTitleCredits
 Course List20 Credits General Education Courses20
 Course List10 Credits English Language Enhancement Courses10
Total:30 Credits

The programme requirements & the courses on offer are subject to amendment


Senior Year Entry

Senior year admission Students will be required to complete around 80 credits. Please refer to the Study Plan.

Study Plan

  • Year 1 Entry
  • Year 3 Entry

Students admitted at the Year 1 Entry Point are required to complete 160 credits and of which no more than 40 credits should be taken at foundation level during the nominal 4-year study period for the degree of Bachelor of Science with Honours in Data Science and Artificial Intelligence.

CategoriesWeightings
Core Computing Courses110 Credits
Project Courses and Elective Courses20 Credits
English Enhancement Courses10 Credits
General Education Courses20 Credits
Total160 Credits
  • Year 1
  • Year 2
  • Year 3
  • Year 4
CodeTitleCategoryCreditsCourse LevelHonours Classification
MATH S141FAlgebra and CalculusCore5Foundation-
STAT S151FProbability and DistributionsCore5Foundation-
COMP S208FIntroduction to Computer ProgrammingCore5Middleb
STAT S261FData Analytics with ApplicationsCore5Middleb
 English Enhancement CourseENG5Depends on selection-
 English Enhancement CourseENG5Depends on selection-
 General Education CourseGE5--
 General Education CourseGE5--
CodeTitleCategoryCreditsCourse LevelHonours Classification
COMP S202FJava Programming FundamentalsCore5Middleb
COMP S203FIntermediate Java Programming and User Interface DesignCore5Middleb
COMP S209FData Structures, Algorithms, and Problem SolvingCore5Middleb
MATH S262FLinear AlgebraCore5Middleb
STAT S251FStatistical Data AnalysisCore5Middleb
STAT S263FBig Data in OrganizationsCore5Middleb
 General Education CourseGE5--
 General Education CourseGE5--

 

CodeTitleCategoryCreditsCourse LevelHonours Classification
COMP S320FDatabase ManagementCore5Highera or b
COMP S333FArtificial Intelligence AlgorithmsCore5Highera or b
COMP S350FSoftware EngineeringCore5Highera or b
COMP S351FSoftware Project ManagementCore5Highera or b
COMP S382FData Mining and AnalyticsCore5Highera or b
COMP S492FMachine LearningCore5Highera or b
STAT S311FTime Series Analysis and ForecastingCore5Highera or b
STAT S366FSAS ProgrammingCore5Highera or b
CodeTitleCategoryCreditsCourse LevelHonours Classification
STAT S461FData Science ProjectProject10Highera or b
COMP S321FAdvanced Database and Data WarehousingCore5Highera or b
COMP S381FServer-side Technologies and Cloud ComputingCore5Highera or b
COMP S460FAdvanced Topics in Data MiningCore5Highera or b
COMP S493FDeep LearningCore5Highera or b
COMP S413FApplication Design and Development For Mobile DevicesElective5Highera or b
ELEC S425FComputer and Network SecurityElective5Highera or b
The programme requirements & the courses on offer are subject to amendment

Students admitted at the Year 3 Entry Point are required to complete 80 credits during the nominal 2-year study period for the degree of Bachelor of Science with Honours in Data Science and Artificial Intelligence.

CategoriesWeightings
Core Computing Courses60 Credits
Project Courses and Elective Courses20 Credits
Total80 Credits
  • Year 3
  • Year 4
CodeTitleCategoryCreditsCourse LevelHonours Classification
COMP S320FDatabase ManagementCore5Highera or b
COMP S333FArtificial Intelligence AlgorithmsCore5Highera or b
COMP S350FSoftware EngineeringCore5Highera or b
COMP S351FSoftware Project ManagementCore5Highera or b
COMP S382FData Mining and AnalyticsCore5Highera or b
COMP S492FMachine LearningCore5Highera or b
STAT S311FTime Series Analysis and ForecastingCore5Highera or b
STAT S366FSAS ProgrammingCore5Highera or b
CodeTitleCategoryCreditsCourse LevelHonours Classification
STAT S461FData Science ProjectProject10Highera or b
COMP S321FAdvanced Database and Data WarehousingCore5Highera or b
COMP S381FServer-side Technologies and Cloud ComputingCore5Highera or b
COMP S460FAdvanced Topics in Data MiningCore5Highera or b
COMP S493FDeep LearningCore5Highera or b
COMP S413FApplication Design and Development For Mobile DevicesElective5Highera or b
ELEC S425FComputer and Network SecurityElective5Highera or b
The programme requirements & the courses on offer are subject to amendment

SSSDP Subsidy

JUPAS Entry

Starting from 2018 admission, the JUPAS entry point of the programme is included in the Study Subsidy Scheme for Designated Professions/Sectors (SSSDP). Eligible students will receive $44,240 subsidy per annum.

This SSSDP programme normally admits students through JUPAS. The JUPAS code is JSSU70.

Please refer to SSSDP's website for eligibility and more information.


Senior Year Entry

For Senior Year entry students, they may supported by Non-means-tested Subsidy Scheme (NMTSS). Eligible students will receive $33,200 subsidy per annum.

Please refer to NMTSS's website for eligibility and more information.


Admission

This programme provides multiple entry points: Year 1 Entry through JUPAS and Senior Year Entry through Direct Application at the HKMU website.

Entry PointsApplication MethodsCode
Year 1 EntryJUPASJSSU70
Senior Year EntryDirect ApplicationBSCHDSAIJS
Admission Requirements

JUPAS Admission

Students should normally have attained in the Hong Kong Diploma of Secondary Education (HKDSE) Examination results of Level 3 or above in Chinese and English, as well as Level 2 or above in Mathematics, Liberal Studies and an elective subject.

Please refer to JUPAS website for more JUPAS admission information

Should there be unfilled intake places after all admission rounds of JUPAS, the SSSDP participating institution will admit local non-JUPAS applicants with a recognized Higher Diploma or Associate Degree via direct admission of no more than 10% of the subsidised places of each selected programme (subject to SSSDP rules that are to be announced).


First Year Tuition Fee *

The amount of subsidy for the JSSU70 programme under the SSSDP is HK$44,240 per annum. The subsidy is tenable for the normal duration of the study programme concerned and is subject to the students' satisfactory fulfilment for progression in the study programme. The government's terms and conditions apply.

Tuition Fee after SSSDP subsidy:

First YearHK$34,080*
TotalHK$136,320*

*Please refer to the JUPAS page for updates and details.

*The estimated tuition fees listed above are for reference only. Tuition fees are charged according to the number of course credits taken by a student. A student will normally take 40 credits in an academic year.

*The subsidy is tenable for the normal duration of the study programme concerned and is subject to the students' satisfactory fulfilment for progression in the study programme


Senior Year Entry

This programme has offered degree articulation opportunities for local Higher Diploma and Associate Degree holders.

The curriculum is designed to be academically rich and practically oriented for preparing local sub-degree holders to become highly competent computing professionals.

Students admitted at a senior year entry point will join other students from Year 1 entry in pursuing of the degree. They can make use of the chance to build a strong personal network with their peers and many alumni of this programme who are doing well in their career.

Senior Entry Admission Requirement

A Higher Diploma or Associate Degree in statistics, data science, artificial intelligence, information technology, and other programmes of which the curriculum includes training in statistics.

Admission Application

Students interested in this programme should apply through non-JUPAS Direct Application. The programme code is BSCHDSAIJS.

Please refer to the program's website for below or more information

  • Application Procedures
  • Online Application
  • Tuition Fees, Scholarships and Financial Assistance
Jonathan Chiu
Marketing Director
3DP Technology Limited

Jonathan handles all external affairs include business development, patents write up and public relations. He is frequently interviewed by media and is considered a pioneer in 3D printing products.

Krutz Cheuk
Biomedical Engineer
Hong Kong Sanatorium & Hospital

After graduating from OUHK, Krutz obtained an M.Sc. in Engineering Management from CityU. He is now completing his second master degree, M.Sc. in Biomedical Engineering, at CUHK. Krutz has a wide range of working experience. He has been with Siemens, VTech, and PCCW.

Hugo Leung
Software and Hardware Engineer
Innovation Team Company Limited

Hugo Leung Wai-yin, who graduated from his four-year programme in 2015, won the Best Paper Award for his ‘intelligent pill-dispenser’ design at the Institute of Electrical and Electronics Engineering’s International Conference on Consumer Electronics – China 2015.

The pill-dispenser alerts patients via sound and LED flashes to pre-set dosage and time intervals. Unlike units currently on the market, Hugo’s design connects to any mobile phone globally. In explaining how it works, he said: ‘There are three layers in the portable pillbox. The lowest level is a controller with various devices which can be connected to mobile phones in remote locations. Patients are alerted by a sound alarm and flashes. Should they fail to follow their prescribed regime, data can be sent via SMS to relatives and friends for follow up.’ The pill-dispenser has four medicine slots, plus a back-up with a LED alert, topped by a 500ml water bottle. It took Hugo three months of research and coding to complete his design, but he feels it was worth all his time and effort.

Hugo’s public examination results were disappointing and he was at a loss about his future before enrolling at the OUHK, which he now realizes was a major turning point in his life. He is grateful for the OUHK’s learning environment, its industry links and the positive guidance and encouragement from his teachers. The University is now exploring the commercial potential of his design with a pharmaceutical company. He hopes that this will benefit the elderly and chronically ill, as well as the society at large.

Soon after completing his studies, Hugo joined an automation technology company as an assistant engineer. He is responsible for the design and development of automation devices. The target is to minimize human labor and increase the quality of products. He is developing products which are used in various sections, including healthcare, manufacturing and consumer electronics.

Course CodeTitleCredits
 COMP S321FAdvanced Database and Data Warehousing5
 COMP S333FAdvanced Programming and AI Algorithms5
 COMP S351FSoftware Project Management5
 COMP S362FConcurrent and Network Programming5
 COMP S363FDistributed Systems and Parallel Computing5
 COMP S382FData Mining and Analytics5
 COMP S390FCreative Programming for Games5
 COMP S492FMachine Learning5
 ELEC S305FComputer Networking5
 ELEC S348FIOT Security5
 ELEC S371FDigital Forensics5
 ELEC S431FBlockchain Technologies5
 ELEC S425FComputer and Network Security5
 Course CodeTitleCredits
 ELEC S201FBasic Electronics5
 IT S290FHuman Computer Interaction & User Experience Design5
 STAT S251FStatistical Data Analysis5
 Course CodeTitleCredits
 COMPS333FAdvanced Programming and AI Algorithms5
 COMPS362FConcurrent and Network Programming5
 COMPS363FDistributed Systems and Parallel Computing5
 COMPS380FWeb Applications: Design and Development5
 COMPS381FServer-side Technologies and Cloud Computing5
 COMPS382FData Mining and Analytics5
 COMPS390FCreative Programming for Games5
 COMPS413FApplication Design and Development for Mobile Devices5
 COMPS492FMachine Learning5
 ELECS305FComputer Networking5
 ELECS363FAdvanced Computer Design5
 ELECS425FComputer and Network Security5