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AI Vibe Coding for Computer Vision

Course Information

  • Sessions 1 day
  • Duration 7.5 hrs
  • Level Intermediate
  • Assessment NA

Venue

Kuala Lumpur: G-3A-02, Suite Pejabat Korporat, KL Gateway, No 2, Jalan kerinchi, Gerbang kernichi Lestari, 59200 Kuala Lumpur, Malaysia
Penang: Jalan Sungai Dua, 11700 Penang, Malaysia.

Course Brochure

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Certification

  • Certificate of Completion from Tertiary Courses - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Courses.

AI Vibe Coding for Computer Vision

Course Code: C592
AI Vibe Coding Series

9 Review(s) | Add Your Review

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What's This Course About

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.

Course Fee

MYR1,100.00

Course Date

Additional Note

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

Disclaimer: The course dates displayed on our website are tentative and subject to trainer availability. We will confirm the final date after checking with the trainer. You are also welcome to email us your preferred date at sales@tertiarycourses.com.my, and we will do our best to coordinate with the trainer's schedule.

Post-Course Support

  • We may provide consultation related to the subject matter after the course.
  • Please email your queries to sales@tertiarycourses.com.my and we will forward your queries to the subject matter experts and get back to you as soon as possible.

Cancellation & Reschedule Policy

  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
  • Note: the venue of the training is subject to changes due to class size and availability of the classroom. The minimum class size to start a class is 3 Pax.

Course Details

Course Details

What You'll Learn

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

Prerequisite

Basic computer and file-management skills are expected. Familiarity with basic programming, data handling and elementary statistics will help you follow the exercises.

Software Requirement

You will need the following for this course:

Install and test the listed software before class. Confirm the required version and account or licence access in your joining instructions. Cloud and AI services may charge subscription or usage fees.

Hardware Requirement

Bring a Windows or Mac laptop supported by the listed software, with a working keyboard and sufficient storage for course exercises.

Bring your own computer and charger, with a reliable internet connection and permission to install the required software. For live online classes, also prepare a microphone or headset.

If you need help arranging a suitable device, contact us before the class to confirm availability.

How to Apply for HRD Corp Funding

For AI Vibe Coding for Computer Vision (C592), ask your employer’s HR or training team to apply. Confirm this programme’s HRD Corp registration and training-provider details with us before applying; funding is subject to employer eligibility, levy availability and HRD Corp approval.

  1. Request a course quotation, confirmed schedule/content and trainer profile. Ask for the registered programme title/number matching this course.
  2. Your employer signs in to e-TRiS and selects Application > Grant > Apply Grant, then the HRD Corp Claimable Courses (SBL-KHAS) scheme.
  3. Select the registered provider/programme; enter confirmed dates, delivery type, venue, employee details and eligible costs. Upload the documents, complete the declaration and submit.
  4. Monitor e-TRiS for queries and approval. Arrange the training dates to meet the required advance approval period before attending.
  5. After training, retain attendance and supporting documents. Coordinate with the provider for its claim approval before submitting any eligible employer claim. Claims must be submitted within six months of completion.

Approval timing (checked 13 October 2026): In-house training requires a 14-day interval after approval. Public training requires three days after approval through 31 December 2026; this returns to 14 days from 1 January 2027. The course must begin within the additional 90-calendar-day window following the applicable advance approval period. Confirm the latest rules before applying.

Official guidance: grant application steps, current requirements and timing and employer claim steps.

Job Roles

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

Trainers

Saeid is co-founder of Skymics Sdn Bhd. He has 8 years of experience in the field of IoT (Internet of Things) and Information Technology. He is a certified IBM IoT Practitioner and instructor, and a Certified Citizen Data Scientist Train-The-Trainer. He has been co-inventor of 3 inventions during the last 4 years.

Review

Customer Reviews (9)

Hands-on and practical 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
Great course materials and well-paced lessons. The exercises really helped me understand the topic. (Posted on 19/12/2024)
Clear and easy to follow 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
Really enjoyed the training. The examples were relevant and the pace was just right. (Posted on 13/12/2024)
Clear and easy to follow 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
Good hands-on training with plenty of examples. I feel much more confident applying these skills now. (Posted on 13/12/2024)
Superb training 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
Great course materials and well-paced lessons. The exercises really helped me understand the topic. (Posted on 14/01/2024)

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