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WSQ - Image and Video Processing with OpenCV

WSQ - Image and Video Processing with OpenCV

Take your skills in visual data analysis to new heights with our WSQ-endorsed course on Image and Video Processing with OpenCV. This in-depth course covers essential topics like object detection, face recognition, and real-time video analysis using OpenCV's powerful libraries. Through hands-on exercises and case studies, you'll learn how to process and analyze visual data, gaining the skills to tackle a range of image and video processing challenges.

By the end of this course, you’ll have acquired a strong foundation in image and video processing using OpenCV. Whether you are an aspiring data scientist, a developer interested in computer vision, or a professional in fields requiring visual data interpretation, this course will provide you with the tools to understand, analyze, and make informed decisions based on visual data.

Learning Outcomes

By end of the course, learners should be able to

LO1: Understand basic vision systems concepts and applications
LO2: Apply image processing with OpenCV
LO3: Implement feature extraction with OpenCV
LO4: Apply machine learning based computer vision methods
LO5: Implement video analytics algorithms with OpenCV
LO6: Evaluate edge vs cloud-based computer vision systems

Course Objectives

Learners will be able to setup and deploy computer vision system using OpenCV

Course Material

A RPI kit set will be loan out to trainee for training use. The kit set on loan will be as follows:

Raspberry Pi 4 Model B 4GB
16G microSD Card preloaded with Raspberry OS.
Raspberry Pi Power Adaptor
USB Camera

Course Brochure

Download WSQ - Image and Video Processing with OpenCV 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
$900	$81.00	$531.00	$351.00

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-2020505925)

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-2020505925

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

Overview of Computer Vision
Computer Vision Industrial Applications
Traditional vs Deep Learning Based Computer Vision

Topic 2: Image Processing

Basic Image and Video Processing
Image Transformation
Image Filtering

Topic 3: Feature Extraction and Description

Understanding Features
Feature Detection

Topic 4: Machine Learning Based Computer Vision

Overview of Convolutional Neural Network (CNN)
Image Recognition
Object Detection
Object Segmentation

Topic 5: Video Analytics

Overview of Video Analytics
Video Analytics Algorithms

Topic 6: Edge Computing Based Vision System

Cloud vs Edge Computing Systems
Edge 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:

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

Computer Vision Engineer
Machine Learning Engineer
Robotics Developer
Augmented Reality Developer
Video Analytics Specialist
Multimedia Developer
Image Processing Engineer
Visual Effects Artist
Software Developer (with a focus on visual applications)
Drone Technology Developer
Biometrics Systems Engineer
Autonomous Vehicle Systems Developer
Medical Imaging Specialist
CCTV and Surveillance Systems Designer
Game Developer.

Trainers

Richard Wan – Richard Wan is an ACLP-certified lecturer with more than 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 degree in Computer Vision and a Bachelor’s in Electrical Engineering and Computer Science from the University of Wisconsin, Madison. He has co-founded several high-tech companies, including Mediaring Ltd (SGX-listed) and E-Book Systems, and has led advanced R&D projects with Singapore’s National Computer Board.

In his OpenCV training, Richard focuses on teaching learners the foundations of image and video processing using Python. His sessions cover image manipulation, object detection, facial recognition, and real-time video analysis, ensuring participants gain both conceptual and practical knowledge. By combining decades of technical expertise with applied teaching, Richard equips learners to build their own computer vision applications using OpenCV.

Shawn Koh Boon Hiap – Shawn Koh is an ACTA-certified trainer, IoT project director, and entrepreneur with over 25 years of experience in software development, project management, and system integration. He has delivered smart office, smart home, and AI/IoT solutions through I.O.T. Workz, while previously holding leadership roles at the Singapore Exchange and ST Electronics. As a Smart Nation ambassador and guest speaker, Shawn actively promotes AI and IoT adoption across education and industry.

In his OpenCV courses, Shawn emphasizes practical, beginner-friendly projects in image and video processing. His training covers integrating OpenCV with IoT and automation systems, enabling learners to apply computer vision in real-world scenarios such as smart monitoring and image-based sensing. With his strong blend of technical expertise and industry leadership, Shawn helps participants explore OpenCV as a powerful tool for business and innovation.

Tan Woei Ming – Tan Woei Ming is an ACLP-certified trainer and data science professional with over a decade of experience in semiconductor and AI-driven analytics. He holds a Master’s in Intelligent Systems from NUS and a First-Class Honours degree in Electrical and Electronic Engineering from NTU. At Micron Semiconductor, he developed IoT-enabled solutions, wafer map recognition systems, and deep learning algorithms for defect detection and process optimization.

In his OpenCV training, Woei Ming focuses on bridging computer vision with AI and data science applications. His sessions introduce learners to image filtering, feature extraction, and real-time video analysis, with applied examples in manufacturing and automation. By integrating academic research with industry use cases, he ensures learners acquire both the technical skills and applied insights to leverage OpenCV effectively in real-world problem-solving.