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SDSC8011 - Social Foundations of Data Science

Offering Academic Unit
Department of Data Science
Credit Units
3
Course Duration
One Semester
Course Offering Term*:
Not offering in current academic year

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

As a large part of the current data used by data scientists are created by or about humans, it is necessary and helpful to introduce to the students of data science social processes and mechanisms underlying human data. In particular, the course focuses on key issues that give rise to various challenges and/or biases in human data such as self selection, social desirability, cognitive limitations, nonindependence, contextual effects, ecological fallacy, and etc. The disposition of these issues will be inherently linked to technical issues such as sampling, measure errors, statistical control, causal inference, and etc. At the end of the course, the students are expected to be able to identify potential human errors or biases in the existing data science literature, develop systematic approaches to addressing the problems, and implement some of the suggested remedies with real world data.

Assessment (Indicative only, please check the detailed course information)

Continuous Assessment: 100%
 
Detailed Course Information

SDSC8011.pdf

Useful Links

Department of Data Science