Three programmes, one coherent path through AI development
Start with Python fundamentals, build through machine learning, and arrive at production-ready AI systems — each programme a complete piece of work in its own right.
Back to HomeHow the programmes are structured
Enquiry & placement
A short conversation to understand your current level and confirm which programme is the right starting point.
Outline review
Full scope, schedule, and deliverables are shared. You have time to review everything before committing.
Active programme
Weekly modules, recorded content, exercises, and regular mentor-reviewed submissions — at a pace that is structured but not rushed.
Portfolio completion
Final project reviewed and signed off. You leave with something real to show for the work.
Python & Data Foundations
A gentle entry programme building practical Python skills and the data-handling techniques used throughout AI work. Suited to learners new to programming who prefer a steady, supported start. Includes weekly exercises, recorded walkthroughs, and a small project to apply what is covered.
The programme moves from the absolute basics of Python syntax through to working with real tabular data using Pandas and NumPy. By the end, you will have written code that loads, cleans, and visualises a dataset — the kind of task that comes up in every subsequent piece of AI work.
What is included
- Python fundamentals — syntax, data structures, functions, files
- Data handling with Pandas and NumPy
- Visualisation with Matplotlib
- Jupyter notebook workflow
- Weekly exercises with written feedback
- Final data project — yours to keep
Process steps
Environment setup and first Python scripts — mentor checks your setup is working correctly
Core Python modules — submitted for review at each stage
Data handling modules — working with real CSV and JSON data
Final project — a data analysis piece on a topic you choose
Best suited for
- Professionals moving toward data or AI roles
- Non-developers who work with data regularly
- Anyone who has tried Python before but not found a supportive structure
Most popular programme
Best suited for
- Python developers ready to add ML skills
- Data analysts wanting to move into modelling
- Graduates who have studied ML theory but not applied it to real data
Practical Machine Learning
A project-led intermediate programme covering common machine learning methods, model evaluation, and how to apply them to real datasets. Learners receive mentor feedback and code reviews along the way. Includes a portfolio piece to demonstrate the skills developed, all at a comfortable pace.
The focus is on the practical loop of building, evaluating, and improving models — not on mathematical derivations. By the end you will have trained, validated, and documented a model that works on real data, with a write-up explaining your decisions.
What is included
- Supervised learning — classification and regression
- Model evaluation and cross-validation
- Feature engineering and selection
- scikit-learn and XGBoost in depth
- Experiment tracking with MLflow
- Code reviews and portfolio project
Process steps
Data exploration and preparation — reviewed against real-world standards
Model building modules — each submitted for written code review
Evaluation and iteration — mentor feedback on model improvement decisions
Portfolio project — a complete ML pipeline with documented rationale
Production AI Systems
An advanced programme on taking models from prototype to working systems, covering deployment, monitoring, and responsible practices. Designed for learners ready for substantial projects with ongoing mentorship and thoughtful career support. The full scope and schedule are explained clearly before joining.
This programme addresses the gap between a working notebook and a system that runs reliably in a real environment. Topics include containerisation, API design, model monitoring, and responsible practices around bias and fairness — each covered in the context of a substantial project you develop throughout.
What is included
- Model deployment with FastAPI and Docker
- Monitoring and drift detection
- Responsible AI — bias, fairness, documentation
- System design for production environments
- Ongoing mentorship throughout
- Thoughtful career support
Process steps
System architecture planning — mentor reviews your approach before you build
Deployment pipeline modules — containerised model serving
Monitoring and responsible practice modules — ongoing feedback
Final deployed system with documentation and career discussion
Best suited for
- ML engineers who have built models and now need to ship them
- Developers adding AI capabilities to existing products
- Technical professionals who want to understand what production AI involves before taking on responsibility for it
Choosing the right programme
Not sure where to start? This table outlines what is covered in each programme. If you are still unsure, just ask — we are happy to help you find the right level.
| Feature | Python Foundations ฿2,600 |
Machine Learning ฿5,200 |
AI Systems ฿8,500 |
|---|---|---|---|
| Python programming | Prior needed | Prior needed | |
| Data handling (Pandas/NumPy) | |||
| Machine learning methods | — | ||
| Model evaluation | — | ||
| Deployment (Docker/API) | — | — | |
| Monitoring & responsible AI | — | — | |
| Mentor feedback | |||
| Portfolio project | |||
| Career support | — | — |
Shared across all three programmes
Data privacy
Learner data is held and used only as needed for programme delivery. Full details in our Privacy Policy.
Written code review
Every submission receives written feedback from a practitioner. Not automated checks — actual commentary on your specific code.
One-day response
Questions sent to mentors are answered within one working day during an active programme.
Transparent scope
Full programme outline, schedule, and deliverables are shared before payment. No surprises.
Updated materials
Content is reviewed and refreshed at the start of each intake to reflect current tools and practices.
Responsible practice
Ethics and responsible AI are core content in the advanced programme — not optional supplementary reading.
All-inclusive, one-time fees
Prices are in Thai Baht. Each fee covers the full programme — all content, mentor feedback, and project review. Payment details are discussed at the enquiry stage.
Python & Data
฿2,600
- Python fundamentals
- Data handling tools
- Weekly feedback
- Final project
Machine Learning
฿5,200
- ML methods in depth
- Code reviews
- Experiment tracking
- Portfolio project
Production AI
฿8,500
- Deployment & monitoring
- Ongoing mentorship
- Responsible AI
- Career support
Not sure which programme to start with?
Send us a brief message describing your background. We will suggest the most suitable programme — no pressure to commit.
Send a Message