The core courses include foundation courses from Computer Science and Statistics, to help students develop an underpinning knowledge for further studies in the Data Science and Engineering discipline. Students will develop skills in mathematics, statistics and computer programming, and acquire a basic understanding of computing fundamentals including database management and machine learning.
The elective courses include a combination of advanced studies in different aspects of data science. There are the advanced statistics courses providing an in-depth training in data modelling, in addition to elective courses on the computing and engineering facets of data science:
Machine learning and AI methodologies
Big data systems and infrastructure
Data-driven computational technologies and applications
Practical data science
Being equipped with sound knowledge in data-intensive domains not only enables students to further explore potential data science and engineering innovations and applications, but also gives them an edge in the job market and their future career development. HKU is a comprehensive university renowned for its strength across many disciplines, and students have the advantage of choosing their domains of interest from diverse options. The new curriculum allows for 72 credits of free electives and students are strongly recommended to do a Minor (or even a Second Major) programme to develop an application area to better support their pursuit in data science.
The curriculum underscores the importance of capstone learning. Students may opt to complete a 6-credit final year project or Data Science in Discipline Project for capstone project experience. While the final year project focuses on research or applied technologies in data science and engineering, the newly introduced Data Science in Discipline Project requires students to work on a capstone project on data science in association with a domain focus.Students are encouraged to identify a data-intensive problem under their minor programme studies, and to implement a data science solution or application for the problem.
The BEng(DS&E) programme also emphasizes putting theory into practice and hence a new capstone design project-based learning course Real-Life Data Science in which students will take on practical work and experience what data scientists go through every day from data wrangling, data modeling to communications of findings, thereby acquiring knowledge of state-of-the-art data science tools/software and the necessary practical skill sets for their future jobs.
