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Course Details
Course Details
What You'll Learn
Topic 1: Overview of IoT Technologies
Key concepts on IoT
Devices used in IoT
IoT communication standards
IoT applications
Topic 2: Microcontroller Programming for IoT
Setup equipment and programming environment
Establish MQTT communication protocol with the cloud server
Topic 3: Sensor data collection and monitoring
Collect sensor data for process control
Setup IoT cloud dashboard to monitor process
Topic 4: Manage Data and Triggers
Trigger actions to control process
IoT security
Assessment
- Written Exam
- Practical Exam
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
- 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 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 of age 21 and above
- From 1 October 2023, attendance-taking for SWDA's (formerly 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 SWDA's (formerly 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), SWDA 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
- Log in to your U Portal account to submit your UTAP application upon completion of the course.
Note
- SWDA 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
Job Roles
- IoT Product Manager
- Innovation Manager
- IoT Solutions Architect
- Smart City Planner
- R&D Specialist
- Business Strategist
- Digital Transformation Lead
- Manufacturing Process Manager
- IoT Data Analyst
- Connected Devices Engineer
- Operations Manager (IoT-focused)
- Smart Grid Specialist
- Home Automation Developer
- Supply Chain Innovation Manager
- Industrial Automation Strategist
Trainers
Trainers
Fritz Lim is an ACTA-certified trainer and experienced educator with over 15 years of teaching in IT, software development, and electronics. With a degree in Electrical and Electronic Engineering from NTU, he has developed and delivered training in Python, Arduino, Raspberry Pi, and microcontroller-based systems for both youths and adults. His portfolio includes web and mobile app development, robotics education, and IoT prototypes using platforms like micro:bit, Arduino, and Makeblock.
In his IoT training, Fritz emphasizes hands-on, project-based learning. He guides learners through microcontroller programming, sensor integration, and device connectivity, helping them design and test IoT prototypes. By combining technical rigor with accessible teaching methods, he ensures learners acquire both the coding and hardware skills needed to build IoT solutions from the ground up.
Richard Wan is an ACLP-certified lecturer and software consultant with over 40 years of experience in software and hardware development, spanning AI, computer vision, and machine learning. He began his programming career with 8-bit computing in the late 1970s and went on to earn his M.Sc. in Electrical Engineering (Computer Vision) from the University of Wisconsin–Madison. His professional contributions include co-founding multiple high-tech companies, pioneering digital publishing technologies, and leading AI-driven software development in healthcare, defense, and manufacturing.
Richard has taught a wide range of technical courses, including machine learning with Scikit-Learn, deep learning with TensorFlow and PyTorch, and computer vision with OpenCV. In predictive analytics, he emphasizes the use of PyTorch for building deep learning models that can forecast trends, detect anomalies, and classify outcomes. His teaching approach blends decades of hands-on development with structured, beginner-friendly instruction, equipping learners with practical skills to transform data into prediction.
Tan Woei Ming is an accomplished data scientist and AI engineer with over 15 years of experience in artificial intelligence, machine learning, and data-driven innovation. Holding a Master’s in Intelligent Systems from the National University of Singapore (NUS) and a First-Class Honours in Electrical and Electronic Engineering from NTU, he has led AI initiatives in predictive analytics, automation, and process optimization across the semiconductor and manufacturing industries. His expertise lies in translating complex AI technologies into practical business applications, enabling organizations to innovate through data insights and intelligent automation.
Shawn Koh Boon Hiap is a ACTA certified trainer and used to be a specialist trainer in RSAF training specialists and officers. He was also invited by Prime Minister Office on Dec 2019 as guest speaker for Smart Nation event held in Downtown East. Throughout his career in the corporate world, he was also coach and mentor to many others, often relinquishing his leadership to take on more challenging tasks after imparting his knowledge and skillsets to his successors. Shawn is skilled in IoT integrations and development, network administration, system administration, website development, software development, multimedia production, information security, entrepreneurship, corporate leadership and project management.
He is a corporate leader and turned as entrepreneur, is the founder of I.O.T. Workz, a Smart Nation ambassador, offering integrated IoT solutions for residential, commercial and industrial. He was a self-learned programmer and won the National Software Competition North Zone Champion in 1990. He developed the first predictive online-data reduction system in 1996 for the Command and Control (C2) Center in RSAF to provide real-time system health monitoring in the data center. He also formed the Ground-Based Radar System team in ST Electronics (InfoSoft) to provide software maintenance for all radar systems in Singapore between 2003 and 2006. He was also the solution architect for multiple generations of Derivatives Clearing Systems, Head of Enterprise Solutions and held a couple of other leadership roles in SGX between 2007 and 2018. Throughout his years of exposure with Technology, he had mastered many different programming languages, acquired electronics troubleshooting skills and earn professional certifications in PMP, Information Security, Linux Administration and many others.
Review
Customer Reviews (15)
- Average Rating: 5.0/5 Review by Course Participant/Trainee
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Trainer is very knowledgeable. (Posted on 6/16/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Average Rating: 4.7/5 Review by Course Participant/Trainee
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N/A (Posted on 6/16/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - willl recommend Review by Course Participant/Trainee
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. (Posted on 4/8/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - will recommend Review by Course Participant/Trainee
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Tan woei ming (Posted on 4/8/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - will recommend Review by Course Participant/Trainee
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. (Posted on 2/3/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
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