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The data-driven era has created strong interest in and a need for analysing, 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 witnessed huge demand for data analysts in both local and global employment markets. However, designing proper data-driven solutions for analysing and interpreting massive amounts of 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 modelling and analysis, and scientific experimental design.
The CDAS programme is designed to develop 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 patterns and insights from large and complex datasets. Therefore, the curriculum of the CDAS programme provides students with a solid foundation in data structure and algorithms, parallel and distributed computing system programming, statistical modelling and analysis, and large-scale statistical inferences.
The CDAS programme emphasizes 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 interests:
Computational Data Science
Computational Physics
Computational Medicine
Computational Social Science
Program overview
Main Subject
Data Science and Artificial Intelligence
Degree
BSc
Study Level
Undergraduate
Study Mode
On Campus
The data-driven era has created strong interest in and a need for analysing, 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 witnessed huge demand for data analysts in both local and global employment markets. However, designing proper data-driven solutions for analysing and interpreting massive amounts of 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 modelling and analysis, and scientific experimental design.
The CDAS programme is designed to develop 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 patterns and insights from large and complex datasets. Therefore, the curriculum of the CDAS programme provides students with a solid foundation in data structure and algorithms, parallel and distributed computing system programming, statistical modelling and analysis, and large-scale statistical inferences.
The CDAS programme emphasizes 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 interests:
Computational Data Science
Computational Physics
Computational Medicine
Computational Social Science
Admission Requirements
24+
80+
80+
30+
1190+
6+
4 Years
Sep
Tuition fees
Domestic Students
5,722 USD
-
International Students
22,891 USD
-
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
Computational Data Science
CUHK, Hong Kong, Hong Kong SAR
# 19QS Subject Rankings
48 monthsProgram duration
22,891 USDTuition Fee/year
Data Science and Artificial IntelligenceMain Subject Area
Program overview
Main Subject
Data Science and Artificial Intelligence
Degree
BSc
Study Level
Undergraduate
Study Mode
On Campus
The data-driven era has created strong interest in and a need for analysing, 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 witnessed huge demand for data analysts in both local and global employment markets. However, designing proper data-driven solutions for analysing and interpreting massive amounts of 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 modelling and analysis, and scientific experimental design.
The CDAS programme is designed to develop 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 patterns and insights from large and complex datasets. Therefore, the curriculum of the CDAS programme provides students with a solid foundation in data structure and algorithms, parallel and distributed computing system programming, statistical modelling and analysis, and large-scale statistical inferences.
The CDAS programme emphasizes 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 interests:
Program overview
Main Subject
Data Science and Artificial Intelligence
Degree
BSc
Study Level
Undergraduate
Study Mode
On Campus
The data-driven era has created strong interest in and a need for analysing, 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 witnessed huge demand for data analysts in both local and global employment markets. However, designing proper data-driven solutions for analysing and interpreting massive amounts of 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 modelling and analysis, and scientific experimental design.
The CDAS programme is designed to develop 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 patterns and insights from large and complex datasets. Therefore, the curriculum of the CDAS programme provides students with a solid foundation in data structure and algorithms, parallel and distributed computing system programming, statistical modelling and analysis, and large-scale statistical inferences.
The CDAS programme emphasizes 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 interests:
Admission Requirements
Tuition fees
Domestic Students
International Students
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
Scholarships to study abroad
Find scholarships to study abroad with our lists of international scholarships – categorized by country, by subject, and by type of student.
Scholarship Applications: Frequently Asked Questions
Get answers to all your questions about scholarship applications, including tips on how to find scholarships and chances of success.
How to get a full scholarship
Looking for a fully-funded scholarship to see you into university? Find out how to boost your chances of getting one.
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