Three courses,
one connected path
Every course is complete on its own, but they are designed to connect. You can start at the beginning or join at the level that matches where you already are.
Back to HomeHow our courses are structured
Modular topics
Each week focuses on one topic. You do not move forward until the current piece is solid. This keeps confusion from accumulating.
Code-first exercises
Every module includes hands-on coding tasks. Reading about Python is not the same as writing it. We weight the balance toward doing.
Feedback cycles
Submitted work gets written instructor feedback at defined points in each course. You can act on the notes before moving to the next topic.
Intro to AI & Python
A welcoming first course covering Python basics, simple data work, and the core ideas behind machine learning. It is designed for people who are curious about AI but have no coding background — not as a fast path to expertise, but as a careful introduction to the concepts and tools you will keep using in every course that follows.
The course runs about eleven weeks at a part-time pace, with practice tasks each week and written feedback from your instructor. You receive a course completion record on finishing.
How the course works
Enrol and receive access to week one materials and the course guide.
Work through each weekly module, complete the practice tasks, and submit for feedback.
Instructor returns written notes within the scheduled window.
After eleven weeks, receive your course completion record.
Practical Model Building
An intermediate course focused on turning data into working models, with attention to evaluation and responsible use. For learners who have foundational Python skills and want to move into applied machine learning work in a structured way, rather than following scattered tutorials without a clear direction.
The course is self-paced with structured milestones. Project tasks give you practice working with data you have not seen before, and code reviews provide specific written notes on your approach.
How the course works
Review the prerequisite checklist; enrol when Python fundamentals are in place.
Work through modules at your own pace, completing project tasks at each milestone.
Submit code for review; instructor returns written notes within the scheduled window.
Complete the final project to close out the course.
Capstone Mentorship Track
A mentored track guiding learners through an applied AI project from initial scoping to a presentable prototype. It is suited to those assembling a portfolio of real work — not just a collection of completed courses, but a project they can explain, demo, and discuss with others.
The track includes scheduled one-to-one sessions with your mentor and participation in a small cohort of fellow learners working on their own projects. Duration is agreed with your mentor based on project scope.
How the track works
Initial session with your mentor to scope the project and agree on milestones.
Work on the project with regular one-to-one check-ins and written feedback at each stage.
Participate in cohort sessions to share progress and give peer input.
Complete and present your prototype at the end of the track.
Help choosing the right one
Not sure where to start? This matrix shows what each course includes so you can compare before deciding.
| Feature | Intro | Model Building | Capstone |
|---|---|---|---|
| Prior experience required | None | Basic Python | Course 2+ |
| Written feedback on tasks | |||
| Code review | |||
| One-to-one mentoring | |||
| Completion record | |||
| Portfolio project outcome | |||
| Price (THB) | ฿3,800 | ฿16,500 | ฿32,500 |
Best for beginners: Intro · Best for practical skills: Model Building · Best for portfolio work: Capstone
Shared standards and practices
Learner data privacy
Course submissions and personal data are stored securely and not shared with external parties.
Annual content review
All course material is reviewed each year. Outdated approaches are replaced; current tools and libraries are kept up to date.
Defined feedback windows
Every course specifies when to expect feedback. You always know the turnaround window before you submit work.
Capped cohort sizes
Intakes are sized so instructors can engage meaningfully with each learner's work, not just manage volume.
Transparent Thai-baht pricing
All prices are in THB with no hidden charges. Payment is made once before course access begins.
Clear terms and conditions
Enrolment terms, refund conditions, and what is included in each course are written in plain language before you pay.
Course fees in Thai baht
One payment per course, no subscription required. Contact us if you have questions about enrolment before you pay.
Intro to AI & Python
- ~11 weeks part-time
- Weekly tasks + written feedback
- Course completion record
- No prior experience needed
Practical Model Building
- Self-paced with milestones
- Project tasks + code reviews
- Responsible AI content
- Requires foundational Python
Capstone Mentorship Track
- One-to-one mentoring
- Learning cohort participation
- Portfolio project outcome
- Scope agreed with mentor
Questions before you enrol?
We are happy to help you pick the right starting point. Send a message or call the Nimmanhaemin office and we will get back to you within one working day.