Three courses, one clear path through AI development
From a welcoming introduction to building and deploying full AI systems — each course is designed to follow the last, with mentor support throughout.
← Back to HomeHow our courses are structured
Each course follows the same approach: short conceptual lessons, hands-on tasks, mentor feedback on your work, and a portfolio piece at the end. The detail and complexity increase across the three levels, but the method stays consistent.
Learn the concept
Short, focused lessons introduce each idea in plain language before any code is involved.
Apply in a task
Guided tasks give you a structured way to use what you just read, with clear starting points.
Receive feedback
Submit your work and a mentor replies with notes on what worked and what to revisit.
Build the portfolio piece
Each course concludes with a project that draws on everything covered and is reviewed by your mentor.
AI Development Foundations
A welcoming starter course for learners new to building with AI. We introduce the essential ideas plainly, show the tools in a friendly step-by-step way, and offer small hands-on tasks so concepts settle naturally. Suited to newcomers and those exploring a change of direction. Includes structured lessons, practice materials, and mentor feedback, at a comfortable pace over roughly eight weeks.
- No prior programming or data science experience required
- Structured lessons with guided practice tasks
- Mentor feedback included throughout
- Portfolio piece at completion
- Responsible AI introduced from the first module
Working with Machine Learning
A hands-on course for learners ready to build and understand models. We move through data handling, training, and evaluation with guided tasks, and support you as you shape a small portfolio piece. Well suited to those comfortable with the fundamentals who want deeper practice. Includes mentor reviews, group discussion, and a scope of around ten to twelve weeks.
- Data preparation, model training, and evaluation covered
- Mentor reviews on each major task
- Group discussion sessions included
- Portfolio piece — a working model with write-up
- Recommended for those who have completed Foundations or equivalent
Complete AI Engineering Track
A comprehensive, mentor-supported track for learners aiming to build and deploy full AI systems. It moves from model development through to serving, monitoring, and responsible practice, centred on a substantial portfolio project you create with guidance. Recommended for dedicated learners preparing for professional roles. Includes regular mentorship, code review, and a thoughtfully paced schedule over several months.
- Full lifecycle: development, serving, monitoring, responsible practice
- Regular 1-to-1 mentorship sessions
- Code review on each major module
- Substantial portfolio project — a deployed AI system
- Suitable for learners who have completed Machine Learning or have equivalent experience
Which course is right for you?
A side-by-side look at what each course covers so you can decide where to start.
| What you need / want | Foundations ฿1,950 |
Machine Learning ฿6,700 |
Engineering Track ฿12,300 |
|---|---|---|---|
| No prior experience | |||
| Comfortable with programming basics | |||
| Understand how ML models work | Intro only | ||
| Build and deploy a full AI system | |||
| Portfolio project included | |||
| Regular 1-to-1 mentorship | Feedback only | Reviews + group | |
| Code review included | Portfolio only | ||
| Responsible AI covered | |||
| Best for | Complete beginners | Learners post-Foundations | Those aiming for professional roles |
Not sure which level is right? Send a message and we will help you decide.
Standards we hold across all courses
Consistent practices that apply whether you are in Foundations or the Engineering Track.
Learner data security
Submitted work and personal details are stored securely. We do not share learner data with third parties.
Two-day feedback target
We commit to returning feedback on submitted tasks within two working days and monitor this across all active learners.
Quarterly curriculum review
Course materials are checked against current tools and industry practice every quarter. Outdated content is replaced, not patched.
Mentor check-ins at defined points
We do not wait for learners to reach out. Mentors check in at course milestones regardless of whether work has been submitted.
Published assessment criteria
Portfolio projects are assessed against criteria you can read before you start building. No surprise scoring.
Responsible AI throughout
Ethics is not a standalone module. It is woven into lessons and tasks at every level from Foundations onwards.
Course fees
All prices in Thai Baht. One-time payment per course, no recurring subscription.
AI Development Foundations
- Structured lessons
- Practice materials
- Mentor feedback
- Portfolio project
Working with Machine Learning
- Data handling & training tasks
- Mentor reviews on tasks
- Group discussion sessions
- Portfolio piece with write-up
Complete AI Engineering Track
- Full lifecycle engineering
- Regular 1-to-1 mentorship
- Code review per module
- Substantial portfolio project
Not sure where to start?
Send us a message describing where you are now and what you are hoping to learn. We will reply with a plain recommendation — no sales pressure.
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