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SDSC3011 - Social Data Processing and Modelling

Offering Academic Unit
School of Data Science
Credit Units
3
Course Duration
One Semester
Pre-requisite(s)
Course Offering Term*:
Semester B 2023/24
Semester B 2024/25 (Tentative)

* 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
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

SDSC3011.pdf