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AI Vibe Coding for Machine Learning

Course Information

  • Sessions 2 days
  • Duration 15 hrs
  • Level Intermediate
  • Assessment NA

Venue

Kuala Lumpur: G-3A-02, Corporate Office Suite, KL Gateway, No. 2, Jalan Kerinchi, Gerbang Kerinchi Lestari, 59200 Kuala Lumpur, 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 Machine Learning

Course Code: C430
AI Vibe Coding Series

8 Review(s) | Add Your Review

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What's This Course About

AI Vibe Coding for Machine Learning shows you how to build, train, evaluate and deploy machine learning models by directing AI coding assistants such as Cursor, GitHub Copilot and Claude. Instead of memorising every library function, you describe your goal in plain English, review the Python code the AI writes and guide it until your model performs well. The course is designed for analysts, developers, engineers and data enthusiasts who want to apply machine learning to real problems faster and with confidence.

You will start by getting started with AI vibe coding for machine learning, setting up your environment and learning how to prompt an AI assistant to load, explore and prepare data with pandas and scikit-learn. Next you will build and train models with AI, covering regression, classification and clustering, feature engineering and train-test splits, and introducing neural networks with TensorFlow or PyTorch. You will then evaluate and improve your models, using appropriate metrics, cross-validation, hyperparameter tuning and techniques to reduce overfitting.

The final topic covers deploying machine learning with AI, packaging your model, serving predictions through a simple API or web app and planning for monitoring and retraining. Throughout the course you will learn to check AI-generated code carefully, understand what each step does and avoid common pitfalls such as data leakage. All exercises are hands-on with real datasets. By the end, you will be able to use AI vibe coding to deliver working machine learning solutions from data to deployment.

Why Take This Course?

  • Hands-On Learning Learn by doing. Every topic is practised hands-on, so you leave with skills you can use at work straight away.
  • Live Coaching Experienced instructors coach you live, answer your questions and guide you step by step.
  • Free Post-Course Consultation Stuck after class? Message your trainer any time for guidance as you apply what you have learned.
  • Always-Updated Materials Materials are refreshed to stay relevant. Log in to our LMS any time to get the latest version.
HRD Corp Claimable

🏦 HRD Corp Claimable

This course is HRD Corp claimable for eligible employers. Grant approval and reimbursement remain subject to HRD Corp requirements, the employer’s available levy and the approved grant details. How the HRD Corp process works →

Course Fee

MYR2,200.00
+ 8% SST

Course Date

Course Time

Course fees are shown before SST. An 8% SST is included in the estimated total during registration.

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 Machine Learning Fundamentals

Topic 2: Data Classification and Performance Evaluation

Topic 3: Regression Analysis and Predictive Modelling

Topic 4: Clustering and Customer or Data Segmentation

Topic 5: Principal Component Analysis and Dimensionality Reduction

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:

Hardware: Windows PC or Mac laptop

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

Machine learning becomes far less intimidating when an AI assistant writes the boilerplate and a seasoned builder explains what the model is actually doing, which is the combination Dr. Alfred Ang offers. Dr. Ang is a full-stack AI developer, Agentic AI solution architect and corporate trainer, and serves as CTO of Tertiary Infotech Academy Pte Ltd, the Singapore training organisation behind Tertiary Courses. Among Dr. Ang's more than 300 public repositories at github.com/alfredang is data-mining-ml-labs, a set of interactive Python and Streamlit labs that let beginners explore data mining and machine learning concepts visually, adjusting parameters and watching results change in real time. Dr. Ang has also built n8n-inventorycontrol, an AI forecasting agent that runs on a local LLM via Ollama to predict stock needs, a stock-analysis dashboard with live price and volume charts, and AI-powered features across production systems such as the ai-exams certification practice platform and the ai-mms course-registration platform serving Singapore, Malaysia and Ghana. Most of this work was written with AI coding assistants in a vibe coding style: describe the goal, let the AI draft the code, then test and refine it with domain knowledge. That approach suits machine learning especially well, because the real skill lies in preparing data, choosing an appropriate algorithm and judging whether the results can be trusted, rather than memorising syntax. Dr. Ang also places strong emphasis on explaining results in plain language, since a model is only useful when managers and colleagues understand what it predicts and why.

AI Vibe Coding for Machine Learning is designed around that insight. The course opens with AI vibe coding and machine learning fundamentals, setting up a Python environment and learning to prompt an AI assistant to load, explore and visualise data. The second topic covers data classification and performance evaluation, building classifiers and interpreting accuracy, precision, recall and confusion matrices. Learners then move to regression analysis and predictive modelling, forecasting numeric outcomes and checking residuals and error metrics. The fourth topic explores clustering for customer or data segmentation, and the final topic introduces principal component analysis and dimensionality reduction to simplify complex datasets. Dr. Ang demonstrates each technique with interactive labs similar to the Streamlit projects in the public portfolio, prompting the AI live and then pausing to explain the code, question the results and fix mistakes. Participants practise on realistic datasets such as sales, customer and operational records, so they learn to recognise over-fitting, data leakage and misleading metrics. No advanced mathematics background is required, though curiosity and a willingness to experiment help a great deal. Analysts, engineers, managers and career switchers will leave with working notebooks, reusable prompts and the confidence to apply machine learning to their own data. Learners also practise presenting their findings in simple charts and short summaries, so the insights from each model can be shared with colleagues and decision makers who do not code. To explore the machine-learning labs and AI projects behind this course, visit Dr. Ang's portfolio at https://github.com/alfredang.

Review

Customer Reviews (8)

Knowledgeable 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
Excellent delivery and good balance between theory and practice. Learned a lot in a short time. (Posted on 09/05/2026)
Highly recommended 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 12/04/2026)
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
Solid content and a supportive trainer. I would definitely sign up for more courses here. (Posted on 17/08/2025)
Exceeded my expectations 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 engaging session. The trainer patiently answered all our questions and gave useful tips. (Posted on 22/07/2025)
Practical and relevant 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 11/07/2025)

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