CS3481 - Fundamentals of Data Science
Offering Academic Unit
Department of Computer Science
Course Offering Term*:
Semester B 2016/17
Semester B 2017/18 (Tentative)
|* The offering term is subject to change without prior notice|
This course aims to explore the important field of data science. The syllabus covers the main techniques in statistical data modelling, and algorithms in data science, which include predictive modelling, cluster analysis, association rule mining and text mining. In addition, different applications of data science techniques in the real world such as web mining, business analytics and health informatics will be discussed.
Assessment (Indicative only, please check the detailed course information)
Continuous Assessment: 50%
Examination Duration: 2 hours
For a student to pass the course, at least 30% of the maximum mark for the examination must be obtained.
Detailed Course Information
|Department of Computer Science|