CS3481 - Fundamentals of Data Science | ||||||||||||
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| * The offering term is subject to change without prior notice | ||||||||||||
Course Aims | ||||||||||||
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: 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 | ||||||||||||
| CS3481.pdf | ||||||||||||
Useful Links | ||||||||||||
| Department of Computer Science | ||||||||||||
