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AI Vibe Coding for Deep Learning

Sessions 2 days
Duration 15 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.

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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 Deep Learning

Course Code: C539

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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.

No funding is available for this course

For WSQ funding, please checkout the details at WSQ - AI Vibe Coding for Deep Learning

Course Fee

$700.00 (GST-exclusive)

$763.00 (GST-inclusive)

Mode of Training

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

Course Date * Course Date

Course Time * Course Time

9:30am - 5:30pm

No. of Participants

Sponsorship

Self-Sponsored
Employer-Sponsored

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: 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 will need the following for this course:

Python 3 – free
Visual Studio Code – free
Google Colab – free, runs in the browser with a Google account
An AI coding assistant with a free tier, e.g. GitHub Copilot Free in Visual Studio Code

Hardware: Windows PC or Mac laptop

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

CY Quah is an ACLP-certified trainer and data science professional with extensive experience in Python, NLP, and machine learning. He has led AI training programs for SAP, Temasek Polytechnic, and IMDA under the SGUnited Mid-Career Pathways initiative, and has delivered corporate workshops on text analytics, recommender systems, and chatbot development. His expertise includes applying NLP tools such as NLTK, spaCy, and Gensim for sentiment analysis, topic modeling, and text classification.

Solomon Soh is an experienced Data Scientist and AI Trainer with a strong record of teaching and mentoring in Python programming, data analytics, and machine learning. Currently a Data Science Trainer with IBM Singapore, he has coached teams on projects involving natural language processing, computer vision, and chatbots, achieving a 96% learner satisfaction rating for his communication and technical expertise. His career spans roles at Workforce Optimizer, Certis Cisco, Ernst & Young, and IQVIA, where he applied Python-driven analytics to improve operations, optimize staffing, and deliver actionable insights. His academic background includes a double degree in Economics and Psychology from Singapore Management University (Summa Cum Laude, triple major in Analytics), an MBA, and a Master’s in Financial Engineering.

Marcel Leng is an ICT professional and educator with strong expertise in machine learning, cryptography, and applied mathematics. He has conducted extensive research and training in AI, data science, and quantum algorithms, and has guided learners in applying advanced computational tools to real-world security challenges.