Computational Data Science

Overview

Computational Data Science  from The Chinese University of Hong Kong 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.

Key facts:

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.