Who We Are
A School Built Around Learning That Lasts
Synaptiq started from a straightforward question: what does it actually take to learn AI development well? Not quickly, not superficially — but in a way that sticks.
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How Synaptiq Came Together
Synaptiq grew out of conversations between a group of practitioners in Chiang Mai who noticed a gap — most resources for learning AI development either assumed too little or moved too fast. People were finishing courses and still not sure how to approach a real dataset or put a model through proper evaluation.
The school launched in 2022 with a single track and a small study group of eight people. The structure was simple: clear modules, reviewed exercises, and a real project at the end. That format worked. Learners came back for the next track. Some joined as mentors later on.
Since then, Synaptiq has grown steadily — not by scaling up fast, but by keeping course groups small enough that feedback is actually personal. The curriculum has been revised with each cohort, shaped by what learners found confusing or useful. That process is ongoing.
Today we offer three tracks — from an entry-level foundations course to a capstone mentorship experience — and our team of practitioners brings together backgrounds in applied machine learning, software engineering, and data science.
Our Mission
To give learners a straightforward path into AI development — one where the work is hands-on, the feedback is honest, and the outcome is skills that hold up outside the classroom.
What We Value
- Clarity over cleverness — explanations should be understandable, not impressive
- Paced learning — absorbing material at a sustainable rate produces better retention
- Honest feedback — reviews are direct, constructive, and specific
- Real artefacts — finishing a track means having something to show
Where We're Based
Our team works from Chiang Mai, Thailand. All courses run online, so learners join from across the region and beyond. Office hours align with Thailand Standard Time (ICT, UTC+7).
The People
Who You'll Work With
Our mentors and curriculum leads all work with AI systems actively. They bring that context into every review and session.
Natcha Korn
Curriculum Lead · ML Engineer
Natcha built the original Foundations track and continues to revise it with each new cohort. Her background is in applied machine learning for natural language tasks.
Prem Wattana
Senior Mentor · Data Engineer
Prem leads code reviews in Track 02 and runs the mentorship sessions in Track 03. He works professionally in data pipeline design and has been with Synaptiq since the second cohort.
Ariya Lao
Mentor · Applied AI Practitioner
Ariya supports learners through capstone projects and handles the structured feedback sessions. Her focus area is model evaluation and deployment in production contexts.
How We Work
Standards We Hold To
These aren't aspirational — they're the practical commitments that shape how we run each course.
Reviewed Exercises
Every exercise submission receives written feedback from a mentor, not just automated scoring. We check for understanding, not just for correct outputs.
Code Quality Reviews
Track 02 and Track 03 include structured code reviews. We look at readability, structure, and engineering habits — skills that matter well beyond the course.
Privacy-First Approach
Learner data stays within the school and is never shared with third parties for commercial purposes. We collect only what is necessary for course delivery.
Small Cohort Sizes
Groups are kept deliberately small so that feedback is personal and mentors can track each learner's progress meaningfully.
Curriculum Updates
The AI field moves. We revise course material regularly to reflect current tools, library versions, and techniques that practitioners actually use.
Project Completion Standard
Each track ends with a real project that has to meet defined criteria. Completion means the work is ready to be shown, not just submitted.
Our Approach
AI Development Education Done Carefully
Synaptiq operates on the understanding that competence in AI development comes from doing the work — not from watching it being done. Each course module includes exercises where learners write, run, and reflect on real code, and where the feedback loop is tight enough to catch misunderstandings before they compound.
The curriculum spans the territory that a practitioner actually navigates: handling data, choosing and training models, evaluating them honestly, and documenting the process clearly. These aren't abstract skills. They're what distinguishes someone who has studied AI from someone who can work with it.
We are based in Thailand and serve learners across Southeast Asia and beyond. Our courses are in English, and the teams of learners we've worked with come from diverse technical backgrounds — some from software development, some from research, some from unrelated fields who wanted a career shift grounded in something real.
The mentors at Synaptiq are selected because they work in the field, not just teach about it. When a learner brings a problem from an exercise, the mentor can usually draw on something they've encountered in an actual project. That practical texture makes the feedback more useful.
If you have questions about our approach, our team, or how a particular track is structured, we're happy to correspond directly. Contact us at [email protected] or call us during office hours.
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Ready to Learn with Synaptiq?
Browse the available tracks or send us a message to talk through which one fits your current background.