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WSQ - Carbon Footprint Management for Sustainability

WSQ - Carbon Footprint Management for Sustainability

Enhance your proficiency in environmental sustainability with our WSQ Carbon Footprint Management for Sustainability course. Aimed at both professionals and organizations, this course offers comprehensive training in measuring, analyzing, and managing carbon emissions. You'll acquire skills in calculating carbon footprints, setting emission targets, and implementing reduction strategies. By the end of this course, you'll be well-equipped to make impactful decisions that drive organizational sustainability while conforming to global standards.

Step into the role of an environmental steward by mastering carbon management practices tailored for modern businesses. The course covers essential topics such as greenhouse gas accounting, emission reduction techniques, and stakeholder engagement for sustainability. Ideal for managers, sustainability officers, and those interested in corporate responsibility, this course provides you with the skillset to lead sustainability initiatives, reduce operational costs, and enhance your organization's reputation for environmental stewardship.

Learning Outcomes

By end of the course, learners should be able to:

LO1: Identify and analyze the potential of ‘hot spots’ for carbon footprint reduction.
LO2: Prioritise carbon footprint reduction.
LO3: Implement carbon footprint reduction plan.

Course Brochure

Download WSQ - Carbon Footprint Management for Sustainability Course Brochure

Skills Framework

This course follows the guideline of Carbon Footprint Management PRE-ENV-4001-1.1 TSC under Precision Engineering Skills Framework

Certification

Certificate of Completion from Tertiary Infotech - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Infotech.
OpenCerts from SkillsFuture Singapore - After passing the assessment(s) and achieving at least 75% attendance, participants will receive a OpenCert (aka Statement of Achievement) from SkillsFuture Singapore, certifying that they have achieved the Competency Standard(s) in the above Skills Framework.

WSQ Funding

WSQ funding is only applicable to Singaporeans and PR. Subject to eligibility, the funding support is subjected to funding caps.

Effective for courses starting from 1 Jan 2024
Full Fee	GST	Nett Fee after Funding (Incl. GST)
		Baseline	MCES / SME
$720	$64.80	$424.80	$280.80

Baseline: Singaporean/PR age 21 and above
MCES(Mid-Career Enhanced Subsidy): S'porean age 40 & above

Upon registration, we will advise further on how to tap on the WSQ Training Subsidy.

You can pay the nett fee (after the WSQ training subsidy) by the following :

SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.Click here to submit SkillsFuture Enterprise Credit

SkillsFuture Credit (SFC)

Eligible Singapore Citizens can use their SFC to offset course fee payable after funding but the $4,000 Additional SFC (Mid-Career Support) cannot be used. Click here for SkillsFuture Credit submission

UTAP

Eligible NTUC members can apply for 50% of the unfunded fee from UTAP, capped up to $250/year and for members aged 40 and above, capped up to $500/year. Click here to submit UTAP

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding.

To check for Post-Secondary Education Account (PSEA) eligibility for this course, Visit SkillsFuture (course code: TGS-2023021099)

Scroll down to “Keyword Tags” to verify for PSEA eligibility.
If there is “PSEA” under keyword tags, the course is eligible for PSEA.

Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form and email to us.

Course Code: TGS-2023021099

Post-Course Support

We provide free consultation related to the subject matter after the course.
Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Course Cancellation/Reschedule Policy

You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commerce.
We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
Note the venue of the training is subject to changes due to availability of the classroom

Course Details

Topic 1: Identifying and Analyzing Carbon Footprint Hot Spots

Overview of ISO:140001 standards
Identify potential carbon footprint hot spots
Carbon footprint calculator
Analyse the potential of ‘hot spots’ for carbon footprint reduction

Topic 2: Prioritising Carbon Footprint Reduction Initiatives

Identify feasible technology to address carbon footprint ‘hot spots’
Methods for projecting carbon reduction potentials
Prioritising carbon footprint reduction initiatives

Topic 3: Implementing Carbon Footprint Reduction Plan

Fundamentals of environment management systems (EMS)
Key components of carbon footprint reduction plans
Develop carbon footprint reduction plans

Final Assessment

Written Assessment - Short Answer Questions (WA-SAQ)
Case Study (CS)

Course Info

Promotion Code

Promo or discount cannot be applied to WSQ courses

Minimum Entry Requirement

Knowledge and Skills

Able to operate using computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

Positive Learning Attitude
Enthusiastic Learner

Experience

Minimum of 1 year of working experience.
Minimum 18 years old

Minimum Software/Hardware Requirement

Software: NIL

Hardware: Windows and Mac Laptops

About Progressive Wage Model (PWM)

The Progressive Wage Model (PWM) helps to increase wages of workers through upgrading skills and improving productivity.

Employers must ensure that their Singapore citizen and PR workers meet the PWM training requirements of attaining at least 1 Workforce Skills Qualification (WSQ) Statement of Attainment, out of the list of approved WSQ training modules.

For more information on PWM, please visit MOM site.

Funding Eligility Criteria

Individual Sponsored Trainee

Employer Sponsored Trainee

Singapore Citizens or Singapore Permanent Residents
From 1 October 2023, attendance-taking for SkillsFuture Singapore's (SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.
Trainee must pass all prescribed tests / assessments and attain 100% competency.
We reserves the right to claw back the funded amount from trainee if he/she did not meet the eligibility criteria.

Singapore Citizens or Singapore Permanent Residents who are DIRECT EMPLOYEE of the sponsoring company.
From 1 October 2023, attendance-taking for SkillsFuture Singapore's (SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.
Trainee must pass all prescribed tests / assessments and attain 100% competency.
We reserves the right to claw back the funded amount from the employer if trainee did not meet the eligibility criteria.

SkillsFuture Credit:

Eligible Singapore Citizens can use their SkillsFuture Credit to offset course fee payable after funding.

PSEA:

To check for Post-Secondary Education Account (PSEA) eligibility, goto mySkillsFuture portal and search for this course code.
Scroll down to "Keyword Tags" to verify for PSEA eligibility.
If there is “PSEA” under keyword tags, the course is eligible for PSEA.
And if there is no “PSEA” under keyword tags, the course is ineligible for PSEA.
Not all courses are eligible for PSEA funding.

Absentee Payroll (AP) Funding:

$4.50 per hour, capped at $100,000 per enterprise per calendar year.
AP funding will be computed based on the actual number of training hours attended by the trainee.

SFEC:

If the Training Provider has submitted an enrolment for course fee grant claim in Training Partners Gateway (TPGateway), SSG would be able to derive SFEC funding based on this record. There is no need for enterprise to submit any claim request and the SFEC claim will be automatically generated and disbursed.
Where there is no such record, eligible employers are required to submit an SFEC claim after course completion via the SFEC microsite.
SkillsFuture Enterprise Credit (SFEC) Microsite

Steps to Apply Skills Future Claim

The staff will send you an invoice with the fee breakdown.
Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
Upload your invoice and click ‘Submit’

SkillsFuture Level-Up Program

The SkillsFuture Level-Up Programme provides greater structural support for mid-career Singaporeans aged 40 years and above to pursue a substantive skills reboot and stay relevant in a changing economy. For more information, visit SkillsFuture Level-Up Programme

Get Additional Course Fee Support Up to $500 under UTAP

The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).

For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)

Steps to Apply UTAP

Note

SSG subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
UTAP support amount will be paid to training provider first and claimed after end of class by learner.

Appeal Process

The candidate has the right to disagree with the assessment decision made by the assessor.
When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
The candidate must lodge the appeal within 7 days, giving reasons for appeal
The assessor can help the candidate with writing and lodging the appeal.
he assessment manager will collect information from the candidate & assessor and give a final decision.
A record of the appeal and any subsequent actions and findings will be made.
An Assessment Appeal Panel will be formed to review and give a decision.
The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
Please click the link below to fill up the Candidates Appeal Form.

Job Roles

Sustainability Officer
Environmental Consultant
Carbon Analyst
Corporate Social Responsibility (CSR) Manager
Sustainable Supply Chain Manager
Environmental, Health, and Safety (EHS) Manager
Energy Manager
Sustainability Reporting Specialist
Green Building Consultant
Waste Management Specialist
Renewable Energy Project Manager
Climate Policy Advisor
Sustainable Procurement Officer
Conservation Planner
Carbon Offset Specialist

Trainers

Dr. Alvin Ang: Dr. Alvin Ang is an AI researcher, technology leader, and educator with deep expertise in artificial intelligence, data science, and ethical innovation. Holding a PhD in Computer Science, he has contributed to research in AI model transparency, algorithmic fairness, and human-centric system design. As an experienced lecturer and consultant, he has trained professionals and students in responsible AI adoption, governance frameworks, and digital ethics. His work bridges academic research with practical implementation to ensure AI systems are both powerful and ethically aligned.

In “Fundamentals of AI Ethics and Responsible AI,” Dr. Ang focuses on helping participants understand the ethical, social, and regulatory dimensions of AI deployment. His sessions emphasize responsible model design, bias mitigation, and compliance with international AI ethics frameworks. By combining research insights with real-world examples, he equips learners to design AI systems that are transparent, accountable, and aligned with human values.

Tan Woei Ming: Tan Woei Ming is a data scientist and AI engineer with over 15 years of experience in machine learning, automation, and intelligent system design. He holds a Master’s in Intelligent Systems from the National University of Singapore and a First-Class Honours degree in Electrical and Electronic Engineering from Nanyang Technological University. Having led numerous AI projects at Micron Semiconductor Asia, he brings a deep understanding of how data-driven technologies impact business, governance, and ethics in real-world environments.

In “Fundamentals of AI Ethics and Responsible AI,” Woei Ming explores the intersection of AI technology and ethical accountability. His sessions focus on model interpretability, data privacy, and fairness in machine learning applications. Through case studies and technical demonstrations, he helps learners recognize ethical risks in AI systems and apply responsible design practices that promote transparency, equity, and societal trust.

Yeo Hwee Theng: Yeo Hwee Theng is a data science and AI strategy leader with extensive experience in driving enterprise AI adoption, governance, and analytics transformation across healthcare, finance, and government sectors. As the Data & Analytics Product Lead at Amplify Health, she oversees large-scale AI deployment and ethical data governance frameworks. She previously served as AI & Data Architect at Huawei International and Senior Data Scientist at DataRobot, leading projects in ethical AI modeling and data-driven decision-making. She holds a Master of Technology in Enterprise Business Analytics from NUS and an Advanced Certificate in Learning and Performance (ACLP).

In “Fundamentals of AI Ethics and Responsible AI,” Hwee Theng emphasizes the design and implementation of ethical AI governance structures. Her sessions explore fairness, accountability, and transparency in AI applications, with a focus on aligning business objectives with responsible innovation. By connecting ethical frameworks to real-world enterprise use cases, she helps professionals build AI solutions that foster trust, inclusivity, and compliance.

Teh Siew Yee: Teh Siew Yee is a digital transformation and data governance expert with over 20 years of experience in analytics, AI strategy, and regulatory compliance. He has led data ethics and AI governance initiatives at organizations such as Standard Chartered, Hewlett-Packard, and TikTok, ensuring that emerging technologies align with corporate responsibility and international standards. He holds a Master of IT in Business (Artificial Intelligence) from Singapore Management University and a Bachelor of Engineering from NTU.

In “Fundamentals of AI Ethics and Responsible AI,” Siew Yee focuses on integrating ethical considerations into the AI lifecycle—from data collection to deployment. His sessions cover policy frameworks, responsible data management, and organizational AI ethics guidelines. By combining technical expertise with policy insight, he equips learners to design and implement ethical AI strategies that balance innovation with accountability and societal impact.