Faculty of Science

Bachelor of Science (Hons) in Business Computing and Data Analytics

Programme Code

JS2910


Year of Entry

Year 3

Mode of Study

Full Time

Duration of Study

2 Years

Medium of Instruction

The medium of instruction for classroom teaching (in all forms) at HKBU is English, except for those courses that are granted exemption.

Fund Type

Government Funded

Class Start Date

September 2025

Annual Tuition Fees

HK$44,500 (local); HK$175,000 (non-local) I

Credits Required for Graduation

128

Programme Description 

The aim of the programme is to nurture the next-generation business leaders for the international job market, equipped with the latest technical knowhow to succeed in fast-changing technologies for business. The programme has the following objectives:

  1. To provide students with a solid knowledge base and skill set in data analytics that enable them to create innovative applications in business organisations, particularly in finance, economics, and consumer/marketing business;
  2. To provide students with good data-driven problem-solving skills and help them to develop an analytical and creative mind for data analytics solution design, management and planning in business organisations;
  3. To equip students with good inter-personal and communication skills for effective collaboration between IT and business units; and
  4. To equip students with a solid knowledge and experience in developing data analytics projects to support their career advancement and further studies in business computing, data analytics or related fields.

Graduates of this programme are expected to possess knowledge and professional skills in essential areas of computer science, economics, finance and decision sciences related to business computing. In addition to all the essential areas, graduates will also possess in-depth knowledge and professional skills in some specific areas in FinTech, Blockchain, Artificial Intelligence, Machine Learning and advanced programming and dataanalytics skills, so as to broaden their awareness in business applications that involves Artificial Intelligence and Big Data Analysis.

Unique Features

  • The programme is co-offered by the Faculty of Science (Department of Computer Science) and the School of Business.
  • The programme is designed with overseas and/or local data analytics internship.


Student Learning Experiences
 

  • Students can opt for international exchange to diversify their learning experiences.
  • Students are able to undertake internship to gain Fintech work experience.
  • Students are able to join an industry mentoring scheme to learn from data analytics professionals or practitioners.


Career Opportunities
 
We expect our graduates' skills to be attractive to many employers: they can start their careers as business communicators, data scientists, data developers, data engineers, database administrators, financial analysts, market researchers, and other IT-related professionals or enage in financial services jobs. The training in this programme would also facilitate their ventures into launching their own businesses.

 

Remark:

  1. Subject to University annual review.

We adopt a holistic approach in selecting applicants on individual merits. Applicants are required to meet the University entrance requirements, English Language requirements and Programme entrance requirements (if any).

 

Associate Degree/ Higher Diploma Students/ Holders

Local final year students or graduates of an Associate Degree/ Higher Diploma programme at an institution recognised by the University are eligible for publicly-funded senior year places. 

 

Transfer Students

Transfer students who are currently enrolled in a Bachelor’s degree or higher degree programmes at a local or non-local university may apply. 


Please note that according to the guidelines of the University Grants Committee (UGC) on inter-institutional transfer of students, repeating of UGC-funded undergraduate study across institutions, irrespective of whether there is a change of programme or discipline, is generally discouraged unless under very exceptional circumstances.