Singapore University of Social Sciences

Wired-Up (SCO153)

Synopsis

In a world saturated with information, individuals, businesses and institutions are constantly exchanging and leveraging data via algorithmic platforms. This course will investigate data, algorithms and their applications (e.g. artificial intelligence, crime prevention, cybersecurity, healthcare, social services), together with the ways these structures and processes bring about socioeconomic ambiguities. Students will be introduced to the various algorithms involved in machine learning, and be equipped with the critical tools to evaluate the political, social and ethical concerns of various data-driven contexts.

Level: 1
Credit Units: 2.5
Presentation Pattern: Every January

Topics

  • Understanding Data
  • Structures & Systems
  • Approaches to Machine Learning
  • Algorithmic Applications
  • Predictive Policies
  • Surveillance & Privacy

Learning Outcome

  • Describe the conceptual development of data and information.
  • Examine the possibilities and problems of algorithmic decision-making.
  • Identify examples of machine learning.
  • Interpret social and economic implications of algorithms and their applications.
  • Develop arguments from case studies.
  • Relate concepts to contemporary issues and debates.
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