Three Courses, One Clear Path
Each course is a complete programme — not a playlist. They connect in sequence, but you can also start at the level that suits you.
Back to HomeHow These Courses Work
All three courses share a consistent design philosophy. Content is introduced gradually, exercises are reviewed by instructors, and learners always know what the next step is.
Weekly Structure
Each week has a clear scope — what to read, what to write, what to submit for review.
Written Feedback
Instructors write specific, useful comments on submitted exercises — not automated pass/fail responses.
Real Environments
Learners work in Python environments they set up themselves, using the same tools used outside the school.
Progressive Path
Course 1 prepares you for Course 2. Course 2 prepares you for Course 3. Each is also complete on its own.
First Steps in AI
A welcoming starting point for people who have never written code or have only dabbled briefly. This course covers Python from the ground up, introduces how data is structured and worked with in tables, and gives learners a clear sense of what machine learning is actually doing — before asking them to use it.
- Python syntax, variables, loops, and functions
- Working with tabular data using pandas
- Introduction to supervised learning concepts
- Weekly exercises reviewed by instructors
- Course completion record on finishing
Duration
~11 weeks, part-time
Level
No prior coding needed
Building & Testing Models
An intermediate course focused on the practical work of creating, evaluating, and improving machine learning models. This course is for learners who already know some Python and want to move into applied ML work. You'll build models from real datasets, learn how to test them properly, and develop the habit of asking good questions about results — not just accepting them.
- Supervised and unsupervised model types
- Training, validation, and test set practices
- Evaluation metrics and how to interpret them
- Hyperparameter tuning with scikit-learn
- Guided projects with written instructor feedback
Duration
Flexible, structured modules
Level
Some Python experience
Guided Project Track
A mentored programme in which each learner completes a full, end-to-end applied AI project. This isn't a template — you choose a problem area, scope it properly with your mentor, build a working solution, and present it. The result is a documented project you can include in a portfolio or discuss in technical interviews.
- Project scoping and planning with your mentor
- One-to-one mentoring sessions throughout
- Access to the learner community for peer support
- Working prototype and documented write-up
- Final presentation preparation and review
Duration
Paced with your mentor
Level
Portfolio-building stage
Which Course Fits Where You Are?
Use this to match your current experience and goals to the right starting point.
| Feature | First Steps | Building & Testing | Project Track |
|---|---|---|---|
| No coding experience needed | |||
| Instructor code review | |||
| Guided project work | Partial | ||
| One-to-one mentoring | |||
| Completion record | |||
| Portfolio project output | |||
| Price (฿) | 3,500 | 15,000 | 30,000 |
| Best for… | Complete beginners | Python learners ready for ML | Portfolio builders |
Applied Across Every Course
These practices apply to all three programmes.
Data Privacy
Learner data is stored securely and used only for course administration. We do not share it with third parties.
Regular Curriculum Review
Material is reviewed at least once per year to reflect current best practices in Python and ML development.
Responsive Support
Questions to instructors receive a reply within one working day. The community space is checked daily.
Standard Open Tools
All courses use Python, NumPy, pandas, scikit-learn, and other widely-available open-source libraries.
Written Study Materials
Every week's content includes written guides and reference notes, not just videos to rewatch.
Pacing Built for Life
Weekly workloads are sized for people with jobs and other commitments — not for full-time students.
Course Fees
All prices are in Thai Baht. Each fee covers the full course including exercises, feedback, and community access.
Course 01
First Steps in AI
฿3,500
Covers the full eleven-week programme, all exercises, weekly instructor feedback, and the completion record.
- Full course content
- Weekly exercise review
- Completion record
- Community access
Course 02 — Popular
Building & Testing Models
฿15,000
Covers all modules, guided projects, written instructor feedback, and completion record.
- Full course content
- Guided project feedback
- Completion record
- Community access
Course 03
Guided Project Track
฿30,000
Covers mentoring sessions, all project support, community access, and the completed portfolio project.
- 1-to-1 mentoring included
- Full project support
- Community access
- Portfolio-ready output
Not Sure Which Course to Start With?
Send us a message with a little about your background and what you're hoping to work toward. We'll give you a straightforward recommendation.
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