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AI Vibe Coding with PyTorch 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 with PyTorch Deep Learning

Course Code: C539
AI Vibe Coding Series

5 Review(s) | Add Your Review

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What's This Course About

Build real deep learning models without writing every line of PyTorch yourself. In this hands-on 2-day course you will use AI coding assistants—Cursor, GitHub Copilot and Claude—to vibe code deep learning workflows end to end: describe the model you want in plain English, let the AI generate the PyTorch code for tensors, training loops and network architectures, then review, debug and iterate with follow-up prompts. You will learn the prompting patterns that keep AI-generated deep learning code correct, trainable and reproducible.

Over four practical topics you will vibe code the full deep learning journey—from PyTorch tensors and autograd, to neural networks for regression and classification, to convolutional neural networks and transfer learning for image recognition, and finally recurrent networks for sequence and time series data. By the end of the course, you will have a portfolio of working PyTorch models and a repeatable AI vibe coding workflow you can apply to any deep learning problem.

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 for PyTorch Fundamentals

  • What Is AI Vibe Coding
  • Setting Up Cursor, GitHub Copilot and Claude for PyTorch
  • Prompting Patterns for Correct Deep Learning Code
  • Vibe Coding PyTorch Tensor Operations
  • Computation Graphs and Autograd with AI Assistance
  • Reviewing and Debugging AI-Generated PyTorch Code

Topic 2 Vibe Coding Neural Networks

  • Neural Network Architectures, Activation and Loss Functions
  • Vibe Coding a Regression Model in PyTorch
  • Vibe Coding a Classification Model with Softmax and Cross Entropy
  • Generating Training Loops, Optimizers and Metrics from Prompts
  • Saving, Loading and Iterating on Models

Topic 3 Vibe Coding Convolutional Neural Networks

  • Overview of CNNs: Convolution, Pooling and Padding
  • Vibe Coding a CNN Image Classifier
  • Diagnosing Overfitting with AI Assistance
  • Data Augmentation and Regularization via Prompts
  • Transfer Learning with Pre-Trained Models

Topic 4 Vibe Coding Recurrent Networks for Sequence Data

  • Overview of RNNs, LSTM and GRU
  • Vibe Coding an LSTM for Time Series Forecasting
  • Tuning Sequence Models with Follow-Up Prompts
  • Evaluating and Visualizing Model Performance
  • Packaging a Complete Deep Learning Project

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:

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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