Programmes
Nowadays, people live in a digitally inclusive society. Human and automated activities continuously generate data that is stored in digital format. These data come from everywhere, including social media, corporate information systems, wearable equipment, etc. The Computational Data Science (CDAS) programme (co-organized by the Department of Computer Science and Engineering and the Department of Statistics) aims to equip students with the latest in large-scale data processing, computational statistics, computer-intensive statistical inference, machine learning, data mining, and data visualization, while also developing the skills to effectively communicate data insights and neatly interpret complex data structures, etc. Such capabilities enable students to develop cutting-edge massive data analytics and management solutions that are of practical interest to academics, industry, and society.
Make Data-Driven
The data-driven era creates strong interests and needs of analyzing, storing, distributing, and sharing massive amounts of data using sophisticated data analytics and machine learning algorithms and methodologies, with applications in multiple disciplines including science, social science, finance, public health, medicine, engineering, and telecommunications. We have already witnessed a huge job demand of data analysts in both local and global employment markets. However, how to design proper data-driven solutions for analyzing and reasoning massive information remains a non-trivial challenge, since it requires in-depth knowledge of both computing methodologies and statistical principles for problem solving, data collection, data modeling and analysis, and scientific experimental design.
The CDAS programme is designed to manufacture mathematical, technical and analytical skills to create solutions to lead data-driven decision making. It aims to equip students with the capabilities of applying both (1) high-performance parallel and distributed computing for big data manipulation, and (2) data-driven statistical procedures, methodologies and theories for mining patterns, making predictions, and discovering sciences from large and complex datasets. Therefore, the curriculum of the CDAS programme provides students with solid foundations of data structures and algorithms, parallel and distributed computing system programming, statistical modeling and analysis, as well as large-scale statistical inference.
The CDAS programme emphasizes on the computational foundations of data science, providing an in-depth understanding of algorithms and data structures for storing, manipulating, visualizing, interpreting and learning from large datasets. Four specialized streams are offered for students to choose application fields according to their own interests:
- Computational Data Science
- Computational Physics
- Computational Medicine
- Computational Social Science
Note that the CDAS programme aims to admit high caliber students who demonstrate outstanding abilities in English, mathematics and science subjects. Excellent academic backgrounds, together with a problem-solving mindset, will be essential to comprehend the knowledge and tackle the future challenges related to global issues.
Published: Summer 2021
Last Updated: Summer 2022