Teaching AI one block at a time
We are a small school with a clear philosophy: understanding beats speed. Learn who we are and how we put that into practice.
Back to HomeHow Modelary came to be
Modelary started in Chiang Mai in 2021 when a small group of developers and educators found themselves frustrated with the options available to adult learners who wanted to understand AI without following a full computer-science degree. The courses that existed tended to be either very shallow crash courses or very deep academic tracks with no middle ground.
The founders built the first version of what became the Intro course for a cohort of eight people — a mix of designers, marketing professionals, and small business owners who were curious about machine learning but had no Python background. The feedback from that cohort shaped everything that came after.
By 2023 we had added the intermediate and mentored tracks, settling into the three-course structure we use today. Our physical office in Nimmanhaemin is small by design. We keep cohorts modest so instructors can give each learner real attention, not automated nudges.
Our mission
To give working adults a clear, honest path into AI development — built around practice, feedback, and realistic expectations about what study produces over time.
Our approach
Modular design, written feedback on real work, and no inflated claims about outcomes. We aim to be a school you could recommend to a friend without hedging.
Our values
Honesty in what we teach and what we promise. Respect for learners' time. A preference for depth over speed. These are not slogans — they inform every curriculum decision.
The people behind the courses
A small team with a mix of software engineering, data science, and adult education backgrounds.
Prem Wiriyasak
Co-founder & Lead InstructorWorked as a data engineer in Bangkok before moving to Chiang Mai to build Modelary. Designs the curriculum and teaches the intermediate track personally.
Nattaya Lertsiri
Curriculum Designer & MentorHas a background in instructional design and spent three years building Python workshops for non-technical teams. Leads the Capstone Mentorship Track.
Somchai Charoenwong
Intro Course InstructorA patient, methodical teacher who has been coding in Python for over a decade. Wrote the Intro course from scratch and runs each new cohort himself.
How we keep quality high
These are the practices we hold ourselves to across every course and every cohort.
Written feedback on every task
Instructors write personal notes on submitted work. We do not rely on automated grading for tasks that require judgment.
Annual curriculum review
The AI field moves fast. We review and update course content each year to reflect what is actually relevant, not just what was accurate when we launched.
Learner data protection
We collect only the information needed to run courses. Learner data is stored securely and never shared with third parties for marketing purposes.
Capped cohort sizes
We limit the number of learners in each intake so instructors can engage with each person's work rather than managing volume.
Post-course feedback loop
Every learner completes a structured review at the end of their course. We read all responses and use them in curriculum planning.
Honest completion records
Completion records describe what was studied and for how long. We do not make claims about employment outcomes that the course itself cannot support.
AI education grounded in practice
Modelary operates in a field that attracts a lot of noise. There is no shortage of online platforms selling speed and status — courses that promise to turn someone into an AI engineer in a few weekends. We are not that kind of school, and we have never tried to be.
What we focus on is the kind of understanding that holds up when you sit down at a computer and try to do something real. Python syntax is learnable in a week; knowing which model to reach for, how to evaluate it honestly, and where the approach breaks down — that takes time and a curriculum designed with those questions in mind.
Our instructors are working practitioners who have spent time building models outside of an academic context. That matters because the gap between theory and practice in applied AI is real, and learners benefit from guidance that acknowledges it.
We are small, based in northern Thailand, and happy to stay that way. Growth for its own sake would require tradeoffs we are not willing to make. A manageable number of learners per instructor is not a limitation — it is the point.
Ready to find your starting point?
Browse the courses or send us a question — we are happy to help you figure out which course makes sense for where you are right now.