In the digital era, following advancements made in innovative technologies, data handling is growing at an unprecedented pace. The data-driven world opens tremendous possibilities and opportunities for companies and businesses for all industries as they can make use of the data information to create values for their business. As a disruptive consequence of the digital revolution, data science and analytics have become an emerging and cross-disciplinary field that requires knowledge and skills in many areas such as computer science, statistics, and mathematics.
The Doctor of Philosophy (Ph.D.) Program in Data Science and Analytics aims to facilitate close integration of statistical analytics, logical reasoning, and computational intelligence in the study of data processing and analytics. The program will provide rigorous research training that prepares students to become knowledgeable researchers who are conversant in applying logic, mathematics, algorithms, and computing power in the process of examining and analyzing data in academia or industry so as to derive valuable insights for making better decisions.
The Ph.D. Program aims to develop the skills needed for students to identify theoretical research issues related to practical applications, formulate and undertake research that addresses issues identified, and independently find a data science and analytics related solution. A Ph.D. graduate is expected to demonstrate mastery of knowledge in the discipline and to synthesize and create new knowledge, making an original and substantial scientific contribution to the discipline.
On successful completion of the Ph.D. program, graduates will be able to:
- Identify scientific and engineering correlations, significances, and insights in new data science and analytics models, algorithms, tools, principles, frameworks, solutions, and techniques;
- Demonstrate critical thinking and analytical skills from the perspective of data science and analytics;
- Apply a range of qualitative and quantitative research methods for data science and analytics;
- Translate and transform fundamental research insights effectively into data science practice in academic fields and industry;
- Exercise independent thinking and demonstrate effective communication skills in presenting and publishing scientific findings; and
- Conduct original research independently and competently showing in-depth knowledge in the field of data science and analytics.
To qualify for admission, applicants must meet all of the following requirements. Admission is selective and meeting these minimum requirements does not guarantee admission.
i. General Admission Requirements of the University
- Applicants seeking admission to a master's degree program should have obtained a bachelor’s degree from a recognized institution, or an approved equivalent qualification;
- Applicants seeking admission to a doctoral degree program should have obtained a bachelor’s degree with a proven record of outstanding performance from a recognized institution; or presented evidence of satisfactory work at the postgraduate level on a full-time basis for at least one year, or on a part-time basis for at least two years.
ii. English Language Admission Requirements
Applicants have to fulfill English Language requirements with one of the following proficiency attainments:
- TOEFL-iBT: 80*
- TOEFL-pBT: 550
- TOEFL-Revised paper-delivered test: 60 (total scores for Reading, Listening and Writing sections)
- IELTS (Academic Module): Overall score: 6.5 and All sub-score: 5.5
* refers to the total score in one single attempt
Applicants are not required to present TOEFL or IELTS score if:
- their first language is English, or
- they obtained the bachelor's degree (or equivalent) from an institution where the medium of instruction was English.
This program is for HKUST(Guangzhou) Pilot Scheme Admission.
For more program information, please refer to pg.ust.hk/programs.
About the School
Located at the Clear Water Bay of Hong Kong, the Hong Kong University of Science and Technology (HKUST) is a research-focused institution that ranks first among top young universities in the world (Ti ... Read More