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 has become an emerging and cross-disciplinary field that requires knowledge and skills in many areas such as computer science, statistics and mathematics.

The Master of Philosophy (MPhil) and Doctor of Philosophy (PhD) Programs in Data Science and Analytics aim to facilitate close integration of statistical analytics, logical reasoning, and computational intelligence in the study of data processing and analytics. The programs 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 MPhil Program aims to expose students to issues involved in the development of scientific, educational and commercial applications of data science and analytics. A graduate of the MPhil program should demonstrate a good working knowledge of issues in the discipline. He or she should be capable of synthesizing and creating new knowledge, making contribution to the field.

The PhD 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 PhD graduate is expected to demonstrate mastery of knowledge in the discipline and to synthesize and create new knowledge, making original and substantial scientific contribution to the discipline.

On successful completion of the MPhil program, graduates will be able to:

1. Demonstrate critical thinking and analytical skills essential for solving real data science problems;
2. Apply a range of qualitative and quantitative research methods for data science and analytics; and
3. Translate and transform advanced research techniques effectively into data science practice in academic fields or industry.

On successful completion of the PhD program, graduates will be able to:

1. Identify scientific and engineering correlations, significances, and insights in new data science and analytics models, algorithms, tools, principles, frameworks, solutions, and techniques;
2. Demonstrate critical thinking and analytical skills from the perspective of data science and analytics;
3. Apply a range of qualitative and quantitative research methods for data science and analytics;
4. Translate and transform fundamental research insights effectively into data science practice in academic fields and industry;
5. Exercise independent thinking and demonstrate effective communication skills in presenting and publishing scientific findings; and
6. Conduct original research independently and competently showing in-depth knowledge in the field of data science and analytics.

1. Minimum Credit Requirement

   MPhil: 15 credits
   PhD: 21 credits

2. Credit Transfer

   Students who have taken equivalent courses at HKUST or other recognized universities may be granted credit transfer on a case-by-case basis, up to a maximum of 3 credits for MPhil students, and 6 credits for PhD students.

3. Cross-disciplinary Core Courses

2 credits

All students are required to complete either UCMP 6010 or UCMP 6030. Students may complete the remaining courses as part of the credit requirements, as requested by the Program Planning cum Thesis Supervision Committee.

4. Hub Core Courses

4 Credits

Students are required to complete at least one Hub core course (2 credits) from the Information Hub and at least one Hub core course (2 credits) from other Hubs.

  Information Hub Core Course

  Other Hub Core Courses

5. Courses on Domain Knowledge

MPhil: minimum 9 credits of coursework
PhD: minimum 15 credits of coursework

Under this requirement, each student is required to take one required course and other electives to form an individualized curriculum relevant to the cross-disciplinary thesis research. Only one Independent Study course may be used to satisfy the course requirements. To ensure that students will take appropriate courses to equip them with needed domain knowledge, each student has a Program Planning cum Thesis Supervision Committee to approve the courses to be taken soonest after program commencement and no later than the end of the first year. Depending on the approved curriculum, individual students may be required to complete additional credits beyond the minimal credit requirements.

  Required Course List

  Sample Elective Course List

To meet individual needs, students will be taking courses in different areas, which may include but not limited to courses and areas listed below.

6. Additional Foundation Courses

Individual students may be required to take foundation courses to strengthen their academic background and research capacity in related areas, which will be specified by the Program Planning cum Thesis Supervision Committee. The credits earned cannot be counted toward the credit requirements.

7. Graduate Teaching Assistant Training

All full-time RPg students are required to complete PDEV 6800. The course is composed of a 10-hour training offered by the Institute of Educational Innovation and Practice (IEIP), and session(s) of instructional delivery to be assigned by the respective departments. Upon satisfactory completion of the training conducted by IEIP, MPhil students are required to give at least one 30-minute session of instructional delivery in front of a group of students for one term. PhD students are required to give at least one such session each in two different terms. The instructional delivery will be formally assessed.

8. Professional Development Course Requirement

Students are required to complete PDEV 6770. The 1 credit earned from PDEV 6770 cannot be counted toward the credit requirements.

PhD students who are HKUST MPhil graduates and have completed PDEV 6770 or other professional development courses offered by the University before may be exempted from taking PDEV 6770, subject to prior approval of the Program Planning cum Thesis Supervision Committee.

Students are required to complete INFH 6780. The 1 credit earned from INFH 6780 cannot be counted toward the credit requirements.

PhD students who are HKUST MPhil graduates and have completed INFH 6780 or other professional development courses offered by the University before may be exempted from taking INFH 6780, subject to prior approval of the Program Planning cum Thesis Supervision Committee.

9. English Language Requirement

Full-time RPg students are required to take an English Language Proficiency Assessment (ELPA) Speaking Test administered by the Division of Language Education before the start of their first term of study. Students whose ELPA Speaking Test score is below Level 4, or who failed to take the test in their first term of study, are required to take LANG 5000 until they pass the course by attaining at least Level 4 in the ELPA Speaking Test before graduation. The 1 credit earned from LANG 5000 cannot be counted toward the credit requirements.

 Students are required to take DLED 5001. The credit earned cannot be counted toward the credit requirements. Students can be exempted from taking this course with the approval of the       Program Planning cum Thesis Supervision Committee.

10. Postgraduate Seminar

Students are required to complete DSAA 6101 and DSAA 6102 in two terms. The credit earned cannot be counted toward the credit requirements.

11. PhD Qualifying Examination

PhD students are required to pass a qualifying examination to obtain PhD candidacy following established policy.

12. Thesis Research

  MPhil:

1. Registration in DSAA 6990; and
2. Presentation and oral defense of the MPhil thesis.

PhD:

1. Registration in DSAA 7990; and
2. Presentation and oral defense of the PhD thesis.

Last Update: 6 July 2023

To qualify for admission, applicants must meet all of the following requirements. Admission is selective and meeting these minimum requirements does not guarantee admission.