Postgraduate Programs 2024/25

Master of Science Program in Data-Centric Artificial Intelligence Technology

GENERAL INFORMATION

Award Title

Master of Science in Data-Centric Artificial Intelligence Technology

Program Short Name

MSc(DCAI)

Mode of Study

Both full- and part-time

Normative Program Duration
Full-time: 2 years
Part-time: 3 years

Program Fee

RMB 298,000

Offering Unit

Data Science and Analytics Thrust Area

Information Hub

Program Advisor

Program Director:
Prof Lei CHEN, Chair Professor of Data Science and Analytics

INTRODUCTION

The Master of Science (MSc) Program in Data-Centric Artificial Intelligence Technology is an elite program providing students with unparalleled academic experience through interplay of advanced domain knowledge and practice in big data and AI. Not only will the program teach students the state-of-the-art knowledge in big data and AI through courses delivered by world-class faculty of the University, but it will also offer students opportunities to work on industry level independent projects. In addition, students will be exposed to real-world industry problems and trained with hands-on experience and essential skillset to apply the cutting-edge knowledge learnt in the courses to tackle the contemporary technology problems facing the industry in the one-year mandatory internship.

Along with the exponential growth in volume and availability of data arising from various forms of new innovations and technologies like 5G, Internet of Things (IoT), mobile devices, etc., enterprises are seeking to leverage the power of data and analysis for driving their businesses strategies and operations, leading to continuous growing demands for highly qualified professionals in the field of data science and AI. This program aims to educate students with academic literacy in big data and AI as well as provide students hands-on experience to work on independent projects and internship in the industry. The program enables students to apply learning to practice, empowering them to be skilled technology leaders and successful big data and AI professionals in the fast-changing business environment.

LEARNING OUTCOMES

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

  1. Develop advanced knowledge and understanding on state-of-the-art big data and AI technologies and analysis methods, such as Data Mining, AI/ Deep Learning, Data Science and Engineering (Database, Hadoop, HDFS, MLOps), Algorithms, Probabilistic Graphical Models (GNN);
  2. Perform various industry data analytics tasks using big data, AI, and computing techniques;
  3. Exercise independent thinking and demonstrate critical analytical skills essential from the perspective of big data and AI;
  4. Investigate existing problems in big data and AI and conduct original big data and AI research independently with in-depth knowledge and practical experience to solve the complex problems in industry; and
  5. Apply a range of big data and AI knowledge and techniques effectively into practice in the academic field and industry for robust data analytics and applications.

CURRICULUM
  1. Minimum Credit Requirement

    30 credits

  2. Credit Transfer

    Subject to the approval of the Program Director and the University regulations governing credit transfer, a maximum of 9 credits can be transferred to the program.

  3. Required Courses

4 credits

DSAA 6010
Industry Round Table
1 Credit(s)
DSAA 6100
Practical Lab Course
3 Credit(s)
  1. Elective Courses

12 credits

DSAA 5002
Data Mining and Knowledge Discovery in Data Science
3 Credit(s)
Description
With more and more data available, data mining and knowledge discovery has become a major field of research and applications in data science. Aimed at extracting useful and interesting knowledge from large data repositories such as databases, scientific data, social media and the Web, data mining and knowledge discovery integrates techniques from the fields of database, statistics and AI.
DSAA 5009
Deep Learning in Data Science
3 Credit(s)
DSAA 5012
Advanced Database Management for Data Science
3 Credit(s)
DSAA 5013
Advanced Machine Learning
3 Credit(s)
DSAA 5020
Foundation of Data Science and Analytics
3 Credit(s)
DSAA 5021
Data Science Computing
3 Credit(s)
  1. Independent Project

6 credits

DSAA 6800
Independent Project
6 Credit(s)

Students are required to complete a six-month independent project on real-world industry problems. Each independent project will be supervised by one academic faculty member. The topics of the projects will come from industry with focus on data analytics. Full-time students are expected to complete the project in the second term of their first academic year. Part-time students are expected to complete the project in the second term of their second academic year.

  1. Internship

8 credits

DSAA 6920
Industry Internship I
2 Credit(s)
DSAA 6921
Industry Internship II
3 Credit(s)
DSAA 6922
Industry Internship III
3 Credit(s)

Students are required to participate in a year-long internship in the industry arranged by the Program Office. Full-time students are expected to complete the internship in the second year of their study. Part-time students are expected to complete the internship in the third year of their study. Each internship will be supervised by one academic faculty member and one industry faculty member as a pair.

The internship consists of three parts. Students are required to pass oral examinations consisting of one Open Topic report, one Intermediate report and one Final report. Each oral presentation should normally take approximately 2 hours. The Open Topic will be examined based on the scientific value, feasibility and technical challenges of the proposed topic; the Intermediate report will assess the student’s progress and industry collaboration progress; the Final report will examine the final output from the internship project and whether the student indeed knows how to apply AI techniques to concrete data science applications.

ADMISSION REQUIREMENTS

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

1. General Admission Requirements of the University

Please refer to Admission Requirements.

2. English Language Admission Requirements

Please refer to Admission Requirements.

3. Additional Information

  • Candidates with the following qualifications are preferred:

  • • A good honors degree in Data Science or AI; or

  • • A good honors degree in a related discipline with 2 years’ experience in IT industry; or

  • • A good bachelor’s degree in Data Science or AI with 2 years’ experience in IT industry.

  • Candidates with Data Analytic background can also be considered.

APPLICATION

Apply online before the application deadlines.

Application Fee

RMB 300

Application Deadlines

For 2024/25 Fall Term Intake (commencing in Sep 2024):

International students*
15 Jun 2024

Chinese students
15 Jul 2024

Application Open On

1 Nov 2023

* All international students are required to obtain a student visa (X visa) for studying in China's mainland. For details on student visa (X visa) requirements, please click here.

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