Singapore University of Social Sciences

Enabling Technologies for Data Science and Analytics: The Internet of Things

Enabling Technologies for Data Science and Analytics: The Internet of Things (MOC005)

Applications Open: To be confirmed

Applications Close: To be confirmed

Next Available Intake: To be confirmed

Course Types: To be confirmed

Language: English

Duration: 6 months

Fees: To be confirmed

Area of Interest: Management

Schemes: To be confirmed

Funding: To be confirmed

School/Department: School of Business


Course: Enabling Technologies for Data Science and Analytics: The Internet of ThingsLink: Institution: Columbia University, New York CityWebsite: https://www.edx.orgDuration: 5 weeks, 7 to 10 hours per weekTotal Learning Hours: Minimum 35 hoursCost: Verified Certificate USD149The Internet of Things is rapidly growing. It is predicted that more than 25 billion devices will be connected by 2020. In this data science course, you will learn about the major components of the Internet of Things and how data is acquired from sensors. You will also examine ways of analyzing event data, sentiment analysis, facial recognition software and how data generated from devices can be used to make decisions.

Level: 5
Credit Units: 1
Presentation Pattern: -


  • Internet of Things 1 (Wireless Communications and Standard)
  • Internet of Things 2 (Networks)
  • Internet of Things 3 (Embedded Systems and Interface, Energy Harvesting, Machine Learning, Cloud Robotics, IoT Economics)
  • Natural Language Processing
  • Audio, Video and Image Processing

Learning Outcome

  • Understand networks, protocols and basic software for the Internet of Things (IoT) and how automated decision and control can be done with IoT technologies
  • Discuss devices including sensors, low power processors, hubs/gateways and cloud computing platforms
  • Learn about the relationship between data science and natural language and audio-visual content processing
  • Study research projects drawn from scientific journals, online media, and novels
  • Review fundamental techniques for visual feature extraction, content classification and high dimensional indexing
  • Review techniques that can be applied to solve problems in web-scale image search engines, face recognition, copy detection, mobile product search, and security surveillance
  • Examine data collection, processing and analysis
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