POSTGRADUATE

DATA SCIENCE
AND ANALYTICS

PHD IN DATA SCIENCE AND ANALYTICS (DSA)

Required Courses

Introduction to Data Science and Analytics
Introduction to Artificial Intelligence
Machine Learning
Introduction to Data Mining
Deep Learning
Database Management Systems
Design and Analysis of Algorithms
Data Science Project
Discrete Mathematics
Mathematics for Data Science
English Communication I for Information Hub Programs
English Communication II for Information Hub Programs
Final Year Capstone Project

Sample Elective Courses

Introduction to Data Science and Analytics
Advanced Probability and Statistics
Machine Learning
Computer Architecture and Systems
Advanced Programming Languages
Discrete Mathematics
Mathematics for Data Science
Introduction to Artificial Intelligence
Cloud Computing and Big Data Systems
Introduction to High-Performance and Parallel Computing
Advanced Algorithms
Introduction to Natural Language Processing and Knowledge
Data Science for Computer Vision and Multimedia
Introduction for Reinforcement Learning
Data Visualization
Data Privacy and Security
Data Science Ethnics
Bayesian Models and Applications
Theories in Computing
Advance Theories in Computing
Theories in Data Science
Deep Learning for Science
Introduction to Optimization
Statistical Inference
Introduction to Data Mining
Advance Machine Learning and Deep Learning
Machine Learning Systems
Data Science for Cross-disciplinary Applications
Special Topics in Data Science
Data Management for Data Science
Complex Data Management
Data Science for Battery Technologies

Program Learning Outcomes

01

Identify scientific and engineering correlations, significances, and insights in new data science and analytics models, algorithms, tools, principles, frameworks, solutions, and techniques.
02

Demonstrate critical thinking and analytical skills from the perspective of data science and analytics.
03

Apply a range of qualitative and quantitative research methods for data science and analytics.
04

Translate and transform fundamental research insights effectively into data science practice in academic fields and industries.
05

Exercise independent thinking and demonstrate effective communication skills in presenting and publishing scientific findings.
06

Conduct original research independently and competently showing in-depth knowledge in the field of data science and analytics.

PHD

General Information

Credit structure:

PhD: 21 credits
Normative Program Duration:

PhD:

Full-time: 3 years (those with a relevant research master’s degree), 4 years (those without a relevant research master’s degree)

Enquiry:

dsat@hkust-gz.edu.cn LEARN MORE ABOUT PROGRAM