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AI Vibe Coding for Deep Learning

Course Information

  • Sessions 2 days
  • Duration 15 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 Deep Learning

Course Code: C539
AI Vibe Coding Series

5 Review(s) | Add Your Review

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What's This Course About

AI Vibe Coding for Deep Learning shows you how to build real deep learning models with PyTorch by directing AI coding assistants such as Cursor, GitHub Copilot and Claude, instead of writing every line yourself. You describe what you want in plain English, review the code the AI produces and guide it until the model works, which lets you focus on understanding the concepts and results. The course is designed for developers, data scientists, engineers and technical learners with basic Python knowledge.

You will start with AI vibe coding for PyTorch fundamentals, setting up your environment and using AI to work with tensors, automatic differentiation, datasets and data loaders. Next you will vibe code neural networks, building, training and evaluating feedforward networks, choosing loss functions and optimisers, and tackling overfitting with regularisation and dropout. You will then vibe code convolutional neural networks for image classification, applying data augmentation and transfer learning with pre-trained models.

The final topic covers recurrent networks for sequence data, including RNNs, LSTMs and GRUs for time series and text, and an introduction to attention and transformers. Throughout the course you will learn to read and check AI-generated code, debug training problems, track experiments and interpret model performance. Every topic is hands-on with real datasets. By the end, you will be able to use AI vibe coding to build, train and improve deep learning models in PyTorch efficiently and with understanding.

Course Fee

MYR2,200.00

Course Date

Course Time

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: AI Vibe Coding and Deep Learning Environment Setup

Topic 2: Neural Networks for Regression and Predictive Modelling

Topic 3: Neural Networks for Data Classification

Topic 4: Convolutional Neural Networks for Image Classification

Topic 5: Transfer Learning and Fine-Tuning Pre-Trained Model

Course Info

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:

You can download and install the following software:

Hardware: Windows and Mac Laptops

Job Roles

Job Roles

  • Machine Learning Engineer
  • Data Scientist
  • Deep Learning Researcher
  • AI Developer
  • Neural Network Designer
  • Computer Vision Engineer
  • NLP Engineer (branching into deep learning)
  • AI Product Manager (technical understanding)
  • Robotics Engineer (with AI components)
  • Bioinformatics Scientist (deep learning applications)
  • Medical Imaging Specialist (AI-focused)
  • Game Developer (AI-driven features)
  • Predictive Analytics Specialist
  • AI/ML Educator or Trainer
  • Autonomous Systems 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 (5)

Great learning experience 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 course content was comprehensive and up to date. The practical exercises were the best part. (Posted on 04/04/2026)
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
Very informative and interactive. The small class size meant we got a lot of personal attention. (Posted on 26/10/2025)
Excellent course 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
A very practical course. The trainer made a complex topic simple and enjoyable to learn. (Posted on 07/09/2025)
Very useful course 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
Solid content and a supportive trainer. I would definitely sign up for more courses here. (Posted on 02/08/2025)
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
The trainer is an expert in the subject and shared many practical insights from real projects. (Posted on 08/08/2024)

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