Nowadays, people live in a digital society. Human and automated activities continuously generate data, storing them in digital format. These data come from everywhere including social media, corporate information systems, wearable equipment, etc. The data-driven era creates strong interests and needs of analyzing, storing, distributing, and sharing massive amounts of data using sophisticated data analytics and machine learning algorithms and methodologies, with applications in multiple disciplines including science, social science, finance, public health, medicine, engineering, and telecommunications. We have already witnessed a huge job demand for data analysts in both local and global employment markets. Besides, how to design proper data-driven solutions for analyzing and reasoning about massive information remains a non-trivial challenge, since it requires in-depth knowledge of both computing and statistical methodologies for problem solving, data collection, data modeling and analysis, and scientific experimental design.
The Computational Data Science (CDASN) programme (co-organized by the Department of Statistics) is designed to manufacture mathematical, technical and analytical skills to create solutions to lead data-driven decision making. Data scientists build intelligent systems to understand, interpret, manage and derive key knowledge from big data sets. It aims to equip students with the latest in large-scale data processing, computational statistics, machine learning, data mining, and data visualisation, while also developing the skills to effectively communicate data insights to key stakeholders, etc. Such capabilities enable students to develop cutting-edge massive data analytics and management solutions that are of practical interest to academics, industry, and society.
The CDASN curriculum emphasizes on equipping students with the following capabilities:
- Effectively collect, clean, manage and analyse large or complex data sets;
- High-performance parallel and distributed computing for massive data management;
- Data-intensive sciences, such as astronomy, biology and physics;
- Data-driven theories and methodologies for mining patterns;
- Making predictions from large and complex datasets, backed by rigorous foundations of data structures and algorithms, statistical modeling and analysis;
- Parallel and distributed computing system programming
Four optional specialized streams are offered for students:
- Computational Data Science
- Computational Physics
- Computational Medicine
- Computational Social Science
Applicants wishing to pursue the programme should apply to JS4416 / CDASN directly.
Applicants seeking admission on the strength of HKDSE examination results should submit their applications via JUPAS. Admission is based on the Best 5 HKDSE subject results with subject weighting applied.
|Admission Requirement||Minimum Level||Subject Weighting|
|Mathematics (Compulsory Part)||4||2|
|Two Elective Subjects||3||#|
# The programme accepts any subject as elective. The preferred subjects (with a subject weighting of "2") include Mathematics Extended Module 1 or 2, Physics, Chemistry, Economics, Information and Communication Technology, Biology, Combined Science; and "1" is given to any other subjects.
Local applicants with other qualifications can apply through the “non-JUPAS admission” scheme. These qualifications include Associate Degree/Higher Diploma, HKALE, GCE, IB, SAT/AP and other overseas qualifications for university admission. Please visit Local Admission Requirement of Office of Admissions and Financial Aid for more details.
International applicants who require a student visa to study in Hong Kong can apply through the “International Students Admissions Scheme”. The applicants must possess relevant high-school or post-secondary qualifications, e.g., GCE-AL, IB, SAT/AP (USA), GSAT (Taiwan), OSSD (Canada), and ATAR (Australia). Please visit Oversea Admission Requirement of Office of Admissions and Financial Aid for more details.
For both schemes, applicants will be considered on the basis of their education background and academic achievements. To make the applications more competitive, applicants are expected to demonstrate outstanding abilities in English, mathematics and science subjects.
Depending on students’ financial situation, or their outstanding performance in academic or other areas, the Government and the University may provide various scholarships and financial aid schemes to support the student’s learning in CUHK.
A press conference was held by Communications and Public Relations Office, CUHK, to introduce the 4 new Bachelor of Science programmes including the BSc in Computational Data Science (JS4416).
- Communications and Public Relations Office, CUHK 香港中文大學傳訊及公共關係處 (Nov 23, 2021) CUHK launches four new Bachelor of Science programmes
- Singtao Daily 星島日報 (Nov 22, 2021) 大學聯招｜中大跨學院新課程 教授生物科技創業
- Topick-HKET 香港經濟日報 (Nov 23, 2021) 【JUPAS】中大3個學院合辦學士學位課程 培育兼具生物科技及商業知識人才
- Takungpao 大公报 (Nov 23, 2021) 生物科技 创业 医疗管理 中大新课程培育跨界全才
- Bastillepost 巴士的報 (Nov 23, 2021) 中大跨學院新課程-教授生物科技創業
- Headline Daily 頭條日報 (Nov 23, 2021) 即時港聞-大學聯招-中大跨學院新課程-教授生物科技創業
- Mingpao 明報 (Nov 23, 2021) 中大3學院合辦新課程-培育生物科技創業人才
- 明報升學網 (Jun 10, 2022) 中大計算數據科學學士課程培養跨學科專才
Our CDAS program was interviewed by Singtao Daily on April 2022.
- Singtao Daily 星島日報 (Apr 12, 2022) 即時港聞-每日雜誌-疫情揭醫療管理不足-大學急培育跨科人才