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Course Details
Course Details
What You'll Learn
Topic 1: Overview of Internet of Things (IoT)
What is IoT?
Sensors and Actuators for IoT
Wireless Communication Technologies for IoT
IoT Applications and Use Cases
Topic 2: Collect and Post Environmental Data to Cloud
What is Cloud Computing
Setup Cloud Computing Account
Collect Environmental Data with Sensors
Transmit Environmental Data using Raspberry Pi
Introduction of Node-Red on Raspberry Pi
Post Data to Cloud using Node-Red MQTT or REST API
Topic 3: IoT Data Analytics and Visualization
Analyze IoT Data on Cloud
Visualize IoT Data on Cloud
Topic 4: Monitor Data to Trigger Control from Cloud
Read Data using Node-Red MQTT or REST API
Trigger Control on Devices
IoT Security
Assessment
- Written Exam
- Practical Exam
Course Info
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:
You will need the following for this course:
- RealVNC Viewer – free
Hardware: Windows PC or Mac laptop
Funding Eligibility Criteria
Self-sponsored learners (individuals)
- Singapore Citizens and Singapore Permanent Residents aged 21 and above.
- Up to 50% course fee funding. Singapore Citizens aged 40 and above receive up to 70% under the Mid-career Enhanced Subsidy (MCES).
- Singapore Citizens aged 25 and above can pay the remaining fee with SkillsFuture Credit.
Company-sponsored learners
- Singapore Citizens and Singapore Permanent Residents who are direct employees of the sponsoring company.
- Up to 50% course fee funding, or up to 70% for employees of SMEs (Enhanced Training Support for SMEs) and for Singapore Citizens aged 40 and above. An SME has no more than 200 employees or an annual turnover of no more than $100 million.
- Employers can also claim Absentee Payroll funding for employees who attend during working hours.
Conditions for all funded learners
- Attendance is taken digitally with Singpass for every session, including the assessment.
- You must complete the course and pass all assessments (assessed as Competent).
- If these conditions are not met, the funding is clawed back and the learner or employer pays the full course fee.
- 9% GST is charged on the full course fee before funding.
- Promo and discount codes cannot be used on funded courses.
- Any balance after funding can be paid in cash, with SkillsFuture Credit, or partly reimbursed by UTAP for NTUC members.
How to Apply SkillsFuture Credit Claim for Individuals
Singapore Citizens aged 25 and above can use their SkillsFuture Credit (base tier) to pay the course fee after funding. The $4,000 mid-career top-up cannot be used for this course.
- Register for this course as self-sponsored and tell us you will use SkillsFuture Credit. Do not pay the amount you plan to claim.
- We email you an invoice showing the course fee after funding.
- From 60 days before the course starts, and no later than the course start date, log in to MySkillsFuture with Singpass and click Claim credits.
- Click Submit a Claim and search for this course by its course code, TGS-2026066740.
- Select your class start date, enter the course fee payable after funding and the amount of credit to claim, then upload the invoice (PDF, JPG or PNG, under 4MB).
- Review, accept the terms and click Agree and Submit. The credit is paid directly to us; processing can take up to 14 working days.
Changing or withdrawing: cancel the claim on MySkillsFuture at least one day before the course starts. If your class date changes, cancel the claim and submit a new one with the new date.
How to Apply UTAP (NTUC Members)
NTUC members can claim 50% of the unfunded course fee under the Union Training Assistance Programme (UTAP), capped at $250 a year (aged below 40) or $500 a year (aged 40 and above). The cap is shared with UTAP claims for AI tool subscriptions.
Eligibility: you must be an NTUC member paying full membership fees, with your membership paid up before and during the course and when you claim. The course must not be fully paid for by your employer or another source.
- Make sure your NTUC membership is paid up before the course starts.
- Register for this course with us and pay the course fee after funding and SkillsFuture Credit.
- Attend at least 75% of the course and sit all assessments.
- Within 6 months after the course ends, go to the NTUC U Portal, open UTAP under E-services, log in with Singpass and choose Course Fee Claim.
- Enter the nett course fee you paid (after all subsidies and SkillsFuture Credit, including GST), and upload your invoice or receipt and your certificate or result slip (PDF, JPG or PNG, up to 5MB each).
- NTUC usually pays the claim within 4 weeks of submission.
Read more in our UTAP guide.
Appeal Process
If you disagree with an assessment decision, you have the right to appeal.
- When the assessor gives you feedback, say whether you agree with the outcome. If you agree, you and the assessor sign the Assessment Summary Record; if you disagree, do not sign it.
- Discuss the decision with the assessor or the assessment manager first.
- If you are still not satisfied, tell the assessor you intend to appeal. The assessor records this in the feedback section of the Assessment Summary Record and informs the assessment manager.
- Lodge your appeal within 7 days, giving your reasons, using the Candidate Appeal Form. The assessor can help you write and lodge it.
- An Assessment Appeal Panel reviews the information from you and the assessor and makes a decision. A record of the appeal and its outcome is kept.
- You will be told the outcome within 2 weeks of lodging the appeal. The panel's decision is final.
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
Mr Tan Woei Ming teaches Tertiary Courses' Arduino and IoT courses with the grounding of an electrical and electronic engineer and the outlook of a data scientist. He graduated with First-Class Honours in Electrical and Electronic Engineering from NTU and holds a Master of Intelligent Systems from NUS, a combination that covers both the embedded hardware that senses the physical world and the intelligent software that interprets it. He previously served as a Data Scientist and later Data Science Lead at Micron Technology, leading AI initiatives in predictive analytics, automation and process optimisation in the semiconductor and manufacturing industries. At Tertiary Infotech he is an Instructor, Software Developer and Agentic Automation specialist, and he is an ACLP-certified trainer who guides beginners patiently through their first hardware projects.
In this CASL course, Mr Tan introduces beginners to the Raspberry Pi as a compact, capable platform for hands-on IoT projects. Learners start with the fundamentals of IoT, from sensors and actuators to wireless communication and practical use cases. They then collect environmental data with sensors on a Raspberry Pi, get to know Node-RED as a visual tool for wiring devices and services together, and post their readings to the cloud using MQTT or REST API. The course continues into analysing and visualising IoT data on the cloud, where Mr Tan draws on his data science background to show how raw readings become useful insight, and then to monitoring data to trigger control of devices, together with essential IoT security. Every session is practical, with Mr Tan guiding learners through wiring, configuration and troubleshooting, so beginners finish with working projects and the confidence to keep experimenting. Learners also see how the same building blocks scale to larger monitoring projects.
Ken Yuen is an ACTA-certified adult educator specialising in STEM education, IoT and embedded systems. He has taught IoT and Raspberry Pi programmes in schools, polytechnics and adult learning institutions, and has conducted WSQ and SkillsFuture courses in Raspberry Pi, Arduino, micro:bit, Jetson Nano and Python. As a Technical Consultant at Anson Engineering he developed IoT-based SCADA and temperature monitoring systems for industrial applications, giving him strong insight into applying Raspberry Pi in industrial contexts. He has an electrical and electronics engineering background from NTU and is an MOE-registered instructor who has taught coding and robotics programmes in over 50 schools.
In CASL - Mastering Raspberry Pi: Hands-On Practical Applications for Beginners, Ken focuses on hands-on experimentation with sensors and automation. His sessions introduce Python programming, GPIO interfaces and IoT integration as learners explore IoT concepts, sensors, actuators and wireless communication technologies. Participants then collect environmental data with sensors, transmit it using the Raspberry Pi and post it to the cloud with Node-RED over MQTT or a REST API. By blending technical depth with practical teaching, Ken ensures beginners build functional prototypes and gain the confidence to use the Raspberry Pi for real-world problem-solving.
Ferris Kwok is a trainer with extensive experience in electronics, robotics and IoT systems development. With a background in microcontroller programming and hardware prototyping, he has trained learners in Arduino, Raspberry Pi and robotics platforms across education and industry settings. Ferris has designed and delivered practical courses that integrate electronics, coding and sensor-based systems, helping learners bridge the gap between theory and applied innovation, and his Raspberry Pi training focuses on hardware setup, GPIO programming and Python-based project development.
In Mastering Raspberry Pi: Hands-On Practical Applications for Beginners, Ferris applies this hands-on IoT experience to a complete sensor-to-cloud workflow. Learners start with the fundamentals of IoT, including sensors, actuators, wireless communication and real-world use cases. They then collect environmental data with sensors, transmit it using the Raspberry Pi and post it to the cloud using Node-RED with MQTT or REST APIs. Participants go on to analyse and visualise IoT data on the cloud, read data back to trigger control of devices, and consider IoT security. With his emphasis on experimentation, beginners gain the confidence to build practical Raspberry Pi projects such as automation systems and basic IoT solutions.
Shawn Koh Boon Hiap is an ACTA-certified trainer, IoT specialist and entrepreneur, and the founder of I.O.T. Workz, which offers integrated IoT solutions for residential, commercial and industrial use. A Smart Nation ambassador, he was invited by the Prime Minister's Office in December 2019 as a guest speaker at a Smart Nation event. His skills span IoT integration and development, software development, network and system administration, information security and project management, and he holds certifications including PMP, Information Security and Linux Administration. He has over 25 years of experience in system integration, project management and software development, including senior roles at the Singapore Exchange and ST Electronics.
In CASL - Mastering Raspberry Pi: Hands-On Practical Applications for Beginners, Shawn draws on the IoT projects he has delivered to emphasise real-world use cases such as smart farming, automation and sensor-based monitoring. Learners begin with an overview of IoT, covering sensors and actuators, wireless communication technologies and applications, then collect environmental data with sensors, transmit it using a Raspberry Pi and post it to the cloud, and are introduced to Node-RED on the Raspberry Pi. His sessions guide participants through setup, Python coding and IoT integration, so they gain practical skills to innovate with embedded systems for business or personal projects.
Richard Wan is an ACLP-certified lecturer with more than 40 years of experience in hardware and software development, specialising in embedded systems, IoT, AI and computer vision. A government scholar, he holds a Master's in Computer Vision and a Bachelor's in Electrical Engineering and Computer Science from the University of Wisconsin, Madison. He has co-founded several technology firms, including SGX-listed Mediaring Ltd and E-Book Systems, and has extensive R&D experience with Singapore's National Computer Board. His Raspberry Pi training emphasises practical, hands-on applications, covering sensor integration, Python programming and real-world IoT projects.
In CASL Mastering Raspberry Pi: Hands-On Practical Applications for Beginners, Richard introduces learners to the fundamentals of embedded systems and IoT through the Raspberry Pi. Participants get an overview of IoT, sensors, actuators and wireless technologies, then collect environmental data with sensors, transmit it using the Raspberry Pi and post it to the cloud with Node-RED via MQTT or REST APIs. They then analyse and visualise IoT data and build prototypes for automation, monitoring and smart applications. Drawing on his technical and entrepreneurial background, he ensures participants gain both theoretical understanding and practical confidence in applying Raspberry Pi solutions.
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good (Posted on 11/22/2021)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 - Trainer is knowledgeable and patient. Review by Course Participant/Trainee
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Trainer is knowledgeable and patient. (Posted on 11/2/2021)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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