SDSC8011 - Social Foundations of Data Science

Offering Academic Unit
School of Data Science
Credit Units
Course Duration
One Semester
Course Offering Term*:
Semester B 2021/22

* 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


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School of Data Science