Home
AI Vibe Coding for Computer Vision

Sessions 1 day
Duration 7.5 hrs
Level Intermediate
Assessment NA

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

Download Course Brochure

Certificate of Achievement from Tertiary Infotech Academy Pte Ltd - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Achievement from Tertiary Infotech Academy Pte Ltd.

AI Vibe Coding for Computer Vision

Course Code: C592

4 Review(s) | Add Your Review

AI Vibe Coding for Computer Vision teaches you how to build computer vision applications in Python by directing AI coding assistants such as Cursor, GitHub Copilot and Claude. Computer vision lets software understand images and video, powering applications such as quality inspection, people counting, document scanning, security monitoring and retail analytics. With vibe coding you describe what you want in plain English and guide the AI as it writes the code, so you can build working solutions quickly. The course suits developers, engineers and technical learners.

You will start by getting set up and covering image processing with AI vibe coding, using OpenCV to load, display, resize, filter and transform images, detect edges and contours, and work with colour spaces and live webcam video. You will learn how to prompt an AI assistant effectively, review the code it produces and fix problems quickly. Next you will move into detection and building vision apps with AI, using pre-trained deep learning models such as YOLO to detect and track objects, recognise faces and read text.

Throughout the course you will turn these capabilities into small, practical applications, such as an object counter or an automated inspection tool, and learn how to evaluate accuracy and performance. You will also consider privacy and responsible use of camera data. Every activity is hands-on with real images and video. By the end, you will be able to use AI vibe coding to build, test and improve computer vision applications confidently.

No funding is available for this course

For WSQ funding, please checkout the details at WSQ - Computer Vision for Beginners

Course Fee

$350.00 (GST-exclusive)

$381.50 (GST-inclusive)

Mode of Training

Physical Classroom Training
Synchronised Teaching using ZOOM
Corporate Training at Company Premise

Add On *

No
Raspberry Pi (4GB) + USB Camera +$200.00

Course Date * Course Date

Course Time *

Sponsorship *

Self-Sponsored
Employer-Sponsored

No. of Participants

Name(s) on Certificate *

Additional Message or Emails for Course Notification

* Required Fields

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

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.

You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
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

Topic 2: Basic Computer Vision Techniques

Topic 3: Image Classification

Topic 4: Object Detection

Topic 5: Computer Vision Systems

Course Info

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

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.

Target Age Group: 21-65 years old

Minimum Software/Hardware Requirement

Software:

Download and Install the following software

Hardware: Window or Mac Laptops

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

Dr Alvin Ang is a ACTA certified trainer. Alvin Ang did his Ph.D., Masters and Bachelors from NTU, Singapore. Previously he was a Principal Consultant (Data Science) as well as an Assistant Professor. He was also 8 years SUSS adjunct lecturer. His focus and interest is in the area of real world data science. Though an operational researcher by study, his passion for practical applications outweigh his academic background. He owns a startup externally

Terence Ee is an experienced IT leader and consultant with more than 25 years of expertise in technology management, information systems, and digital transformation. He has served as Chief Information Officer at the Supreme Court of Singapore and Vice President of Information Systems at Senoko Energy, where he led major IT modernization projects. Since 2017, he has worked as an independent consultant and ACLP-certified trainer, specializing in guiding SMEs and enterprises in adopting future-ready digital platforms. As a WSQ-accredited trainer, Terence delivers programs in digital collaboration, IT governance, and productivity tools. His facilitation emphasizes case studies, simulations, and hands-on practice, enabling learners to apply modern IT systems such as Microsoft 365 and Google Workspace to improve collaboration and business efficiency. With his leadership background and deep IT expertise, Terence prepares learners to thrive in digitally transforming environments.

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.

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.

Ken Yuen is an ACTA-certified adult educator specializing in STEM education, IoT systems, and programming. With a background in electrical and electronics engineering from NTU, he has conducted WSQ and SkillsFuture courses in Arduino, Raspberry Pi, micro:bit, Jetson Nano, and Python. He is also a registered MOE instructor, having taught coding and robotics programs in over 50 schools, equipping students and professionals alike with practical IoT and programming skills. In his IoT courses, Ken focuses on hands-on experimentation with microcontrollers, sensors, and automation systems. His prior experience as a Technical Consultant at Anson Engineering saw him develop IoT-based SCADA and temperature monitoring systems for industrial applications, giving him strong industry insight. By blending educational expertise with technical project experience, Ken ensures learners develop the confidence to build, test, and apply IoT solutions in real-world contexts.

Review

Customer Reviews (4)

Excellent Course and Trainer Review by Course Participant/Trainee

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

Course materials and knowledge of trainer is very adequate.

Saw some reviews on initial set up taking half a day and splitting the no. of course days..
Personally feel 1.5 days will be the best duration but I do prefer to keep it to 1 day.

Most of my set up was done prior to the class, if you know you are attending a programming course and bringing your own laptop, the best way to prepare is to look for an IDE, download the latest patches, etc. before the actual course date.

Not professional to pin the blame on others if it is something we ourselves can prevent in the first place. However, it goes the same for the training provider, if the laptop is being provided, then it should be made ready-to-use.

Would recommend this course! The trainer could adapt and structure the learning according to what I shared I would be using it for, and after learning about my level of coding competency. (Posted on 8/22/2023)

will recommend Review by Course Participant/Trainee

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

. (Posted on 8/12/2020)

will recommend Review by Course Participant/Trainee

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

The initial setup took almost half a day. (Posted on 2/25/2020)

Will Recommend Review by Course Participant/Trainee

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

Better split the course to two day.Is quite complicated programming course. Lucky you have a outstanding and professional Lecturer and I am attend alone. Else will be not enough time to complete the entire lesson

I don't mind course fee increase if can split it to two days. Can provide a basic camera module to participant to apply in the course.
(Posted on 8/27/2018)