Learning AI should feel like building something real.
Mindforge was founded in Bangkok with a simple conviction: that AI skills develop through practice, feedback, and honest expectations — not passive watching.
Back to HomeStarted in a Chatuchak office. Still here.
Mindforge opened its doors in 2019 at a modest office on Phaholyothin Road. At the time, most AI education available in Thailand was either too theoretical for working adults, or too shallow to build real competence. The gap was obvious.
Three of us — a software engineer, a data analyst, and a former lecturer at Chulalongkorn University — put together a curriculum that treated learners as adults capable of doing hard things, given the right structure and support. The first cohort was eight people sitting around a shared table with laptops.
Since then, the tracks have evolved considerably. The curriculum is now written and reviewed by practitioners, not by a committee trying to cover every trending topic. We update it when something genuinely changes in how people build AI systems — not on a marketing calendar.
We're still in the same building, still accepting small cohorts, still doing code reviews by hand. The scale has changed; the approach hasn't.
What we're actually trying to do
Build real capability
Each track produces something you've made yourself. Not copied, not pre-built. Understanding that holds up when you apply it somewhere new.
Be honest about what learning takes
AI development is not a weekend skill. We tell learners this upfront. Our tracks are paced for depth; they ask for consistent effort over weeks, not hours.
Keep the teacher-student relationship central
Mentors at Mindforge are practitioners, not chat interfaces. Questions get real answers. Code gets real reviews.
Who runs Mindforge
A small team with backgrounds in software engineering, applied ML, and curriculum design.
Apirak Suthiwong
Co-founder · Lead Mentor
Apirak spent eight years as a software engineer before shifting to applied ML research. He designed the AI Craftsmanship Track and leads its mentor sessions personally.
Nattiya Thanaporn
Co-founder · Curriculum Director
Nattiya lectured in computer science at Chulalongkorn University for five years. She oversees curriculum structure across all three tracks and runs the Beginner's Workbench.
Krisada Pattanapong
Data & ML Mentor
Krisada joined Mindforge in 2021 after four years in data analytics at a Bangkok fintech. He mentors the Hands-On ML Studio cohorts and reviews portfolio projects.
How we keep the curriculum honest
These aren't aspiration statements. They're operating rules we apply when writing and reviewing every track.
Code review on every project
No track progresses without mentor review of submitted work. Feedback is written, specific, and returned within five working days.
Annual curriculum review
We review each track's technical content once per year against current tools and practices in the field. Outdated material gets replaced, not archived.
PDPA compliance
Learner data is handled under Thailand's Personal Data Protection Act. We collect only what's needed for course administration and never share it for commercial purposes.
Small cohort sizes
Tracks cap at 20 learners per cohort so mentors can provide genuine attention. When demand exceeds capacity, we open a waitlist rather than overcrowd a session.
Transparent track prerequisites
Each track page states clearly what prior knowledge is needed. We'd rather turn someone away from the wrong track now than see them struggle through content that doesn't fit their level.
Post-track learner feedback
Every cohort completes a structured survey at the end. Results are reviewed by the curriculum team and used in the next annual revision cycle.
What we believe about AI education
AI development is a craft. Like most crafts, it takes longer to learn than most marketing copy suggests. At Mindforge, we build tracks around that reality rather than fighting it. The Beginner's Workbench Track does not rush from zero to model deployment in a weekend. The Hands-On ML Studio does not skip the hard parts of understanding why a model behaves as it does. The AI Craftsmanship Track treats system design as something worth slowing down over.
Bangkok has a strong community of developers and data professionals. Many of them came to us having tried other courses and found the material either too shallow to use, or too dense to follow without guidance. The format we settled on — project-first, mentor-reviewed, paced for consistency over speed — addresses both of those problems directly.
We believe that the best thing an AI school can do is help learners build something they understand well enough to explain. Portfolio work matters not because it impresses people, but because the process of finishing it, defending your choices, and taking feedback is how technical confidence actually forms.
Our location on Phaholyothin Road in Chatuchak puts us at the edge of one of Bangkok's most active districts. In-person workshops, when they run, draw from the surrounding tech community. Online participants join the same community channel, attend the same review sessions, and work through the same projects. The learning experience is the same regardless of where you sit.
Talk to us before you enrol
We're happy to answer questions about tracks, workload, and what level is the right starting point for you.
Contact Mindforge