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Short Course

AI for Sustainability: A Technology Perspective

Course ScheduleDuration (days)Mode of DeliveryTGS Reference Number
To be advised2Classroom Learning-

Course Overview

Sustainability is essential to the long-term well-being of all people and communities across our planet. A sound understanding of the fundamental principles of sustainability is therefore crucial to ensure good practices are promulgated and challenges identified. Sustainability is an expansive subject that encompasses varying aspects, and data is essential in parsing the complexities of this multi-faceted topic. The proliferation of data, and the advent of artificial intelligence tools, have opened new possibilities in the analysis of environmental datasets, to guide decision making for important sustainability hypotheses.

This course covers the intersection of these two dominant topics of the 21st century. We will look at how we can employ AI models to tackle specific sustainability challenges.

Through this course, participants will gain a better understanding of how techniques like machine learning and deep learning can be applied towards pressing sustainable problems today.

Course Objectives

At the end of the course, participants will be able to:

  • Understand foundational sustainability concepts
  • Appreciate key challenges in ensuring sustainability
  • Gain knowledge of AI, machine learning and deep learning models
  • Apply these models for specific sustainability problems
  • Analyse model outputs to interpret results, and inform interventions for sustainability issues

Prerequisites

The minimum entry requirement is a general diploma.

Enquire

Funding Available

  • SkillsFuture Funding
  • Enhanced Training Support
  • SkillsFuture Credit
  • SFEC
  • PSEA

    • Instructors


    Dr Edmund Low

    Dr Edmund Low

    A/Prof Edmund Low is currently Associate Professor with NUS College at the National University of Singapore. He has nearly 20 years of academic and professional experience in the use of data-driven tools to answer questions in sustainability and the environment. His past projects include applying AI techniques and mathematical models for climate change mitigation and environmental impact assessment. He is the founding coordinator of the Reasoning with Data pillar at NUS College, and teaches courses on statistical methods, data science and machine learning. As an educator, A/Prof Low is a multiple recipient of both his faculty’s and NUS’ Teaching Excellence Awards. He holds a PhD in Environmental Engineering from Yale University.

    Course Fees


    Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
    39 years old
    or younger    		 40 years old
    or older
    Full Course Fee S$1,900.00 S$1,900.00 S$1,900.00 S$1,900.00 S$1,900.00
    Less: SSG Grant Amount S$1,330.00 S$1,330.00 S$1,330.00 S$1,330.00 -
    Nett Course Fee S$570.00 S$570.00 S$570.00 S$570.00 S$1,900.00
    9% GST on Nett Course Fee S$51.30 S$51.30 S$51.30 S$51.30 S$171.00
    Total Nett Course Fee Payable, including GST S$621.30 S$621.30 S$621.30 S$621.30 S$2,071.00
    Less Additional Funding - S$380.00 - S$380.00 -
    Total Nett Course Fee Payable, including GST, after additional funding from the various funding schemes S$621.30 S$241.30 S$621.30 S$241.30 S$2,071.00
    1. Total nett course fee payable, including GST, after additional funding from various funding schemes.
    2. Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
    3. The applicable funding is for Singaporeans and Singapore PRs. This is subject to change and in accordance with SSG funding guidelines as of course commencement.
    4. For more information on class cancellations and refunds, please visit our Terms and Conditions page.