Programmes
Three Programmes, Designed to Connect
Each programme is complete on its own. Together, they form a path from first script to portfolio project — taken at whatever pace suits you.
← Back to HomeOur Methodology
How the Programmes Are Structured
Each programme follows a submit-feedback-revise loop rather than a watch-and-move-on approach. Learners complete a task or project, submit it to their mentor, receive written feedback, and then revise the work before proceeding. This cycle is the core mechanism through which understanding develops.
All material is delivered digitally. There are no cohort start dates or synchronous sessions to attend on a fixed schedule, though optional check-in calls are built into the Capstone level. Learners set their own weekly pace within a broad timeframe agreed at enrolment.
Complete a task
Receive feedback
Revise and proceed
Programme 01
Foundations of AI Development
An introductory programme covering programming basics, data handling, and core machine learning concepts through small guided projects. No prior coding experience is assumed. By the end, learners can read, write, and reason about Python code for data tasks, and have completed two or three guided projects with documented outcomes.
- Python syntax, data types, and control flow
- Working with tabular data using pandas
- Introduction to scikit-learn for simple classification
- Writing readable, commented code from the outset
- Two guided mini-projects with mentor feedback
Typically 6–10 weeks
฿3,400
Process
- Environment setup and first Python scripts
- Data loading and exploration exercises
- Guided project 1: data cleaning and summary
- Introduction to classification with feedback
- Guided project 2: simple model and write-up
Programme 02
Applied Machine Learning Program
A hands-on course where learners build and evaluate practical models on real datasets with mentor feedback throughout. This programme assumes comfort with Python basics and introduces the full model development process — from exploring a new dataset to evaluating a trained model and documenting the decisions made along the way.
- Exploratory data analysis on real, unpolished datasets
- Regression, classification, and clustering approaches
- Model evaluation metrics and iterative improvement
- Feature engineering and selection techniques
- Project documentation to portfolio standard
Typically 8–14 weeks
฿17,500
Process
- Dataset selection and initial exploration
- Preprocessing and feature engineering
- Model selection with documented rationale
- Evaluation, iteration, and mentor review
- Final project write-up and submission
Programme 03
Capstone Mentorship Program
Extended one-to-one mentoring as learners plan and deliver a substantial portfolio project. This is the most open-ended of the three programmes. Learners propose or develop a project concept in consultation with their mentor, then work through the full lifecycle — research, design, implementation, evaluation, and presentation — with regular mentor contact throughout.
- Project scoping and feasibility review with mentor
- Weekly or fortnightly video check-in sessions
- Written feedback on all intermediate deliverables
- Support through technical blockers and design decisions
- Final presentation preparation and rehearsal
Duration by agreement
฿30,500
Process
- Initial scoping call and project brief
- Research phase with milestone check-in
- Implementation with regular review sessions
- Evaluation, documentation, and iteration
- Final presentation and portfolio submission
Comparison
Which Programme Suits You?
| Foundations | Applied ML | Capstone | |
|---|---|---|---|
| Prior coding needed | Python basics | ML experience | |
| Named mentor | |||
| Written feedback on submissions | |||
| Video call sessions | |||
| Open-ended project topic | |||
| Real dataset projects | Guided | ||
| Programme fee | ฿3,400 | ฿17,500 | ฿30,500 |
Best for
Complete beginners to coding and ML
Best for
Learners who can code but are new to ML
Best for
Learners ready to build their own ML project
Shared Standards
What Applies Across All Programmes
Data Privacy
Learner information is handled in line with our published Privacy Policy and kept separate from any third-party systems.
Response Time
Written feedback on submitted work is returned within three working days for all programme levels.
Annual Review
Programme materials are reviewed and updated annually to reflect current tools and approaches in the field.
Consistent Mentor
One named mentor per learner throughout the programme — not a rotating pool of reviewers.
Fees
Programme Pricing
All fees are one-time per programme. No subscriptions, no hidden charges.
Foundations
฿3,400
One-time programme fee
- Guided mini-projects
- Named mentor
- Written feedback
- Digital materials
Applied ML
฿17,500
One-time programme fee
- Real dataset projects
- Named mentor
- Written feedback on all work
- Portfolio documentation
- Instalment option available
Capstone
฿30,500
One-time programme fee
- Open-ended personal project
- Video call sessions included
- Full mentor support throughout
- Presentation preparation
- Instalment option available
Not Sure Where to Start?
Send us a message describing your current level and what you are hoping to build. We will suggest the programme that makes the most sense as a starting point.
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