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WSQ - Computer Vision for Beginners

WSQ - Computer Vision for Beginners

Unlock the potential of visual data with our WSQ-endorsed Computer Vision for Beginners course. This foundational course is designed to introduce you to the basics of computer vision, from image analysis to object detection. Through hands-on exercises, you will learn how to manipulate images and videos using a variety of techniques and tools, laying the groundwork for more advanced studies in the field.

By the end of this course, you'll have a strong understanding of the core principles of computer vision. Whether you aim to deepen your knowledge in data science or apply visual data in your professional field, this course serves as your stepping stone. You'll be well-equipped to understand, interpret, and make data-driven decisions based on visual information.

Course Objectives

Learners will be able to setup and deploy computer vision system

Learning Outcomes

By end of the course, learners should be able to

LO1: Understand basic vision systems concepts and applications
LO2: Apply basic computer vision techniques
LO3: Implement image classification
LO4: Implement object detection and video analytics
LO5: Evaluate edge and cloud-based computer vision systems

Material

A RPI kit set will be given out to trainee for training use. The kit set consists of the following:

Raspberry Pi 4 4GB RAM Board
Power Adaptor
16G microSD Card
HDMI Cable
USB Camera

Course Brochure

Download WSQ - Computer Vision for Beginners Brochure

Skills Framework

This course follows the guideline of Computer Vision Technology ICT-DIT-4022-1.1 TSC under ICT 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
$1000	$90.00	$590.00	$390.00

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. Please inform us if you intend to use your PSEA funding.

To check for Post-Secondary Education Account (PSEA) eligibility for this course, Visit SkillsFuture (course code: TGS-2020504540)

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-2020504540

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: Overview of Computer Vision with Deep Learning

Introduction to Computer Vision
Computer Vision Business Applications
Classical vs Deep Learning Computer Vision

Topic 2: Basic Computer Vision Techniques

Setup Portable Mini Computer Board
Setup Camera
Setup OpenCV
Image Processing with OpenCV

Topic 3: Image Classification

Introduction to Deep Learning and Neural Network
Overview of Convolutional Neural Network (CNN)
Pre-Trained Vision Models
Image Classification with Pre-Trained CNN

Topic 4: Object Detection

Overview of Single Shot Detector (SSD) Object Detection Technique
Object Detection and Video Tracking with SSD
Overview of YOLO Object Detection Technique
Object Detection and Video Tracking using YOLO
Basic Video Analytics

Topic 5: Computer Vision Systems

Edge Based Vision System
Cloud Based Vision System

Final Assessment

Written Assessment - Short Answer Questions (WA-SAQ)
Practical Performance (PP)

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:

You can download and install the following software:

OpenCV

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 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

Data Scientist
Machine Learning Engineer
AI Researcher
Robotics Engineer
Computer Vision Engineer
Image Processing Specialist
Software Developer (with a vision focus)
Biometrics Specialist
AR/VR Developer
Video Analytics Developer
Autonomous Systems Engineer
Smart Camera Developer
Medical Imaging Specialist
Surveillance System Designer
Visual Effects (VFX) Artist

Trainers

Richard Wan – Richard Wan is an ACLP-certified lecturer with over 40 years of experience in software and hardware development, specializing in AI, computer vision, machine learning, and embedded systems. 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. Richard has co-founded several high-tech companies, including Mediaring Ltd (listed on SGX) and E-Book Systems, and has extensive R&D experience at Singapore’s National Computer Board.

As a trainer, Richard has taught Python, machine learning, deep learning, and computer vision frameworks such as OpenCV, TensorFlow, and PyTorch. His teaching emphasizes practical applications, from image classification to object detection, ensuring learners understand both the theory and implementation of computer vision systems. With his vast experience across healthcare, manufacturing, and defense, Richard equips participants with industry-relevant skills to design and deploy beginner-level computer vision applications.

Tan Woei Ming – Tan Woei Ming is an ACLP-certified trainer and data science professional with over a decade of experience in semiconductor and manufacturing analytics. He holds a Master’s in Intelligent Systems from NUS and a First-Class Honours degree in Electrical & Electronic Engineering from NTU. At Micron Semiconductor, he developed IoT-enabled cloud solutions, wafer map pattern recognition models, and deep learning algorithms for scratch detection and root cause analysis.

In his computer vision training, Woei Ming focuses on bridging AI concepts with hands-on implementation. His courses cover image processing, CNN-based classification, and pattern recognition using Python and R, enabling learners to build foundational skills in computer vision. By integrating his academic research and real-world industry projects, he ensures learners gain both conceptual clarity and applied skills to solve problems using computer vision.

Koh Boon Hiap (Shawn) – Shawn Koh is an ACTA-certified trainer, entrepreneur, and IoT/AI solutions expert with more than 25 years of experience in software development, project management, and system integration. He holds a Master’s in Technopreneurship and Innovation from NTU and a Bachelor’s in Computer Science from SIM, alongside certifications in PMP, Linux Administration, and Information Security. As IoT Project Director at I.O.T. Workz Pte. Ltd., he has delivered smart office, smart home, and IoT lab solutions for schools and enterprises, and he has been invited as a Smart Nation guest speaker on IoT and AI.

In his computer vision courses, Shawn emphasizes practical, beginner-friendly applications such as image classification, object detection, and integration with IoT systems. His training approach blends coding exercises with real-world examples, ensuring participants understand how computer vision is applied in automation, smart systems, and everyday technologies. By combining technical depth with hands-on teaching, Shawn equips learners to confidently explore the fundamentals of computer vision.