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DSC3011 - Social Data Processing and Modelling

Offering Academic Unit
Department of Data Science
Credit Units
3
Course Duration
One Semester
Pre-requisite(s)
DSC1001* and DSC2001

 *Pre-requisite DSC1001 will be exempted for students who are enrolled in Minor in Data Science
Equivalent Course(s)
SDSC3011
Course Offering Term*:
Not offering in current academic year

* The offering term is subject to change without prior notice
 
Course Aims

This course provides students with an extensive exposure to the elements of data processing and modelling for social media. Topics include human error detection, missing data handling, record aggregation, data integration, categorical variable modelling, multivariate data modelling, multilevel data modelling, latent data modelling, temporal data modelling, and spatial data modelling.


Assessment (Indicative only, please check the detailed course information)
Continuous Assessment: 50%
Examination: 50%
Examination Duration: 2 hours
Min. Continuous Assessment Passing Requirement: 30%
Min. Examination Passing Requirement: 30%
 

Note: To pass the course, apart from obtaining a minimum of 40% in the overall mark, a student must also obtain a minimum mark of 30% in both continuous assessment and examination components.

 
Detailed Course Information
DSC3011.pdf