A school built for people who take AI development seriously.
We work from Bangkok with a straightforward mission: structured, substantive courses for practitioners who want to develop real AI skills rather than surface-level familiarity.
Back to HomeHow Garuda Tech came to be
Garuda Tech started from a straightforward frustration. A small group of developers working in Bangkok kept running into the same problem: the AI courses available online ranged from introductory material aimed at absolute beginners to dense academic content that assumed a research background. There wasn't much in between — and not much that was designed around the schedule of someone already working full time.
The school grew from that gap. We started with one course on applied ML fundamentals in early 2022, ran it with a small cohort of twelve learners, collected a lot of feedback, rebuilt parts of it, and ran it again. The current offering reflects several iterations of that process. We added the AI Ethics course after repeated conversations with learners who found that technical depth alone didn't prepare them for the questions that come up in real-world AI development. The Full-Stack AI programme came later, once we were confident we could support a longer engagement with the kind of structure it needed.
We're based at our Sukhumvit office in Bangkok and work with a small team of instructors and mentors who hold active roles in AI development, data engineering, and software architecture. None of our courses are produced to fill a catalogue — each one exists because we thought carefully about what it should teach and how.
The people behind the courses
Our instructors hold working roles in AI and software development. They write and teach the courses, review assignments, and run mentor sessions.
Krit Panitchakorn
Works as a machine learning engineer at a Bangkok-based fintech company. Designed the Recommender Systems course and leads the full-stack programme curriculum.
Siriporn Lertchai
Researches AI governance and policy at Chulalongkorn University. Wrote the AI Ethics and Responsible Practice course and reviews all written reflections.
Nattawut Wongsri
Senior software architect with twelve years in backend and infrastructure. Leads peer code review sessions and mentors learners in the full-stack programme.
Standards we hold ourselves to
These aren't aspirational statements — they're the specific practices we follow in designing and delivering every course we offer.
Clear prerequisites stated upfront
Every course page states what prior knowledge is needed — in plain terms. We don't obscure requirements that would affect whether a learner is ready.
Written feedback on assignments
Assignments receive written instructor feedback, not automated scores. Feedback is returned within five business days of submission.
Data privacy — PDPA compliant
All learner data is handled in accordance with Thailand's Personal Data Protection Act. We do not share learner information with third parties for any marketing purpose.
Realistic time estimates
We publish weekly time commitments that reflect actual learner experience, not optimistic minimums. We update these figures after each cohort based on feedback.
Practitioner-reviewed curriculum
Course content is reviewed by working AI practitioners before each cohort. We revise material that no longer reflects current practice in the field.
No claims we can't support
We don't make career outcome claims we can't substantiate. Our marketing reflects what the courses are — not what we'd like learners to imagine they might become.
Substantive AI learning for working developers in Thailand and across Southeast Asia
AI development as a discipline covers a genuinely wide range of concerns — mathematical foundations, software engineering practices, system design, ethical considerations, and the specific domain knowledge that shapes how a model should behave in a particular context. Courses that try to address all of these lightly tend to leave learners with a fragmented understanding that doesn't translate well into practical work.
Our approach is to narrow scope deliberately. Each course or programme covers a defined domain with enough depth to be useful — not a survey. The AI Ethics course doesn't try to also be an introduction to machine learning. The Recommender Systems course assumes that learners already know ML fundamentals and builds on them rather than rehearsing them.
We designed our programmes with the schedules of working professionals in mind. Online delivery means learners based anywhere in the region can participate, and we schedule mentor sessions and office hours to suit Bangkok time — which also works well for much of Southeast Asia.
The Full-Stack AI Application Programme is our most demanding offering. We designed it for software engineers who already have professional experience and want to integrate applied AI into their practice. The programme's twelve-to-fifteen hour weekly commitment is a deliberate design decision — the kind of depth it covers can't be compressed into a few hours a week without losing what makes it worthwhile.
Ready to look at the courses?
Browse what we offer, or send us a message if you'd like to talk through which track makes sense for your background.