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AI Vibe Coding for Machine Learning

Course Information

  • 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.

Course Brochure

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Certification

  • 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 Machine Learning

Course Code: C430

105 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.

Funding Options

No funding is available for this course

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

Course Fee

$700.00 (GST-exclusive)
$763.00 (GST-inclusive)

Course Date

Course Time

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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.

Post-Course Support

  • 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.

Cancellation & Reschedule Policy

  • 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

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

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

Richard Wan is an ACLP-certified lecturer and software consultant with over 40 years of experience in software and hardware development, spanning AI, computer vision, and machine learning. He began his programming career with 8-bit computing in the late 1970s and went on to earn his M.Sc. in Electrical Engineering (Computer Vision) from the University of Wisconsin–Madison. His professional contributions include co-founding multiple high-tech companies, pioneering digital publishing technologies, and leading AI-driven software development in healthcare, defense, and manufacturing. Richard has taught a wide range of technical courses, including machine learning with Scikit-Learn, deep learning with TensorFlow and PyTorch, and computer vision with OpenCV. In predictive analytics, he emphasizes the use of PyTorch for building deep learning models that can forecast trends, detect anomalies, and classify outcomes. His teaching approach blends decades of hands-on development with structured, beginner-friendly instruction, equipping learners with practical skills to transform data into prediction.

Dr Alvin Ang is a ACTA certified trainer. Alvin Ang did his Ph.D., Masters and Bachelors from NTU, Singapore. Previously he was a Principal Consultant (Data Science) as well as an Assistant Professor. He was also 8 years SUSS adjunct lecturer. His focus and interest is in the area of real world data science. Though an operational researcher by study, his passion for practical applications outweigh his academic background. He owns a startup externally

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.

Review

Customer Reviews (105)

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
Probably more time to practice non standard case studies

Trainer is knowledgeable and extremely willing to share (Posted on 7/22/2020)
might recomemnd 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 platform to run the codes if very slow and inefficient. Would be better to teach students how to run on their on computers.
Would be better to also specify the minimum requirements or pre-requisite for students such as a basic understanding of mathematical functions, especially for the machine learning portion of the course

Trainer today speaks very fast and it makes it hard to follow at times. He also does not go through the code together the students preferring to let the students explore by themselves before asking if they are unsure. May not be the best teaching method especially since classes are not in person (Posted on 6/17/2020)
will recommend 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
Today's lesson was very heavy on statistical methods, one that i do not have background in. I think the first two days instead of introduction to python, it can be converted to introduction to statistical methods. The difference in nature is very big between Day 1-2 (Programming) and 3 (Statistical).

Minimum requirement for the course should be JC (trainer did mention a lot about subjects being covered in JC or Uni) in order for attendees to comprehend the topic.

Prefers to have more hands on, and visual representations of the topics being taught. (Posted on 6/17/2020)
will recommend 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
. (Posted on 6/13/2020)
wil recommend 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
. (Posted on 3/19/2020)

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