// about_codethicket
We built the school
we wished existed.
Codethicket started as a small team in Chiang Mai with a simple goal: make applied AI education honest, hands-on, and genuinely usable by working people.
← Back to Home// our_story
Where Codethicket came from
Codethicket was put together in 2021 by a small group of developers and educators who kept noticing the same pattern: people wanting to learn AI development would wade through dozens of hours of content and come out the other side still unsure how to write anything useful.
The founders had spent years working on applied machine learning projects across Southeast Asia and kept running up against the same gap — there were plenty of courses covering theory, but far fewer that helped learners actually produce and iterate on working code.
So we built from the opposite direction. We started with the kinds of projects a learner would be proud to show someone at the end of a course, and worked backwards to figure out exactly what fundamentals they needed to get there. That structure — practical outcome first, foundational material second — is still at the centre of everything we write.
Our base in Chiang Mai shapes the way we approach learning design. The city has an unusually active developer community, and working alongside that community helped us understand which kinds of course material actually sticks and which kinds tend to get abandoned halfway through.
We keep the school deliberately small. Every course is maintained by the same instructors who wrote it, which means updates happen when the field changes rather than when a content calendar says they should. The mentored Advanced programme pairs each learner with one of those same instructors rather than routing questions to a shared inbox.
That is the kind of school Codethicket is — specific, maintained, and built to produce actual output rather than completion metrics.
// mission_values
What we stand behind
Honest Scope
Every course page tells you exactly what you will and will not learn before you decide to enrol. No inflated descriptions.
Practical First
If a concept cannot be demonstrated by writing and running code, we question whether it belongs in the curriculum at all.
Kept Current
Course material is reviewed regularly. When a library changes or a better approach emerges, we update the content rather than leaving outdated lessons in place.
// our_team
The people behind the courses
Nattawut Kanchanarat
Lead Instructor & Co-founder
Applied ML engineer with eight years building data pipelines and classification systems. Wrote the Model Building course from scratch in 2022.
Siriporn Wongchai
Curriculum Designer & Co-founder
Background in technical writing and instructional design. Responsible for making sure the material reads clearly and the exercises are actually solvable.
Ravi Prakash
Senior Mentor
Software engineer from Bangalore, now based in Chiang Mai. Leads mentorship sessions in the Advanced programme and reviews code submissions.
// standards
How we maintain quality
Exercise Testing
All exercises are run against a clean environment before each course update to confirm they produce the expected output without errors.
Data Privacy
Learner data is held only for course delivery and communication. We do not share personal information with third-party marketing services.
Version Control
Course material is versioned. Learners enrolled in a course always have access to the version they started, and can opt into updated editions.
Feedback Loops
We read every piece of learner feedback and use it directly to revise confusing sections or add clarifying examples.
Instructor Consistency
Mentorship sessions in the Advanced programme are always handled by the same instructor assigned at enrolment, not rotated across a shared pool.
Clear Documentation
Every course includes written notes alongside video or interactive segments, so learners can reference material without rewatching.
// expertise
Applied AI education built around working code
Codethicket operates at the point where software development practice and machine learning meet. The courses are designed for people who want to write code that does something with data — not for people who want to read about what code could theoretically do.
The introductory material covers Python in the context of data handling: reading files, shaping data, writing functions that process inputs and return outputs. From there, the Model Building course moves into training loops, evaluation metrics, and the practical work of diagnosing why a model is not performing as expected. The Advanced programme goes further, treating each learner's project as the primary unit of work rather than a side activity.
All three courses are written and maintained by people who use the same tools in their own work. That means the choice of libraries, the structure of the exercises, and the kinds of problems used as examples all reflect how applied AI development actually works — not how it looks in academic papers or marketing decks.
Codethicket is based at 30/7 Chang Khlan Road in Chiang Mai and can be reached by phone or email for enquiries about course content, enrolment, or the mentorship programme.
Ready to see the courses?
Browse what we teach or get in touch if you have questions before deciding.