Teaching AI with clarity, not hype.
We built Neuronest because the best way to learn machine learning is to work through it step by step, with someone checking your reasoning along the way.
← Back to HomeHow Neuronest came to be
Neuronest was started in Chiang Mai in 2021 by a small group of practitioners who had spent several years building data systems and teaching informally at local tech meetups. The recurring observation was that most online AI courses either moved too fast or relied heavily on motivational language over substance. We wanted to try something different.
We designed the first course, First Steps in AI Coding, as a low-pressure eight-week track for working adults with some coding background. The structure was simple: short, plainly titled lessons, small practical tasks, and written feedback from a human rather than an automated checker. The response from early participants told us the approach was worth developing further.
By 2023 we had added the Hands-On Machine Learning course, and in 2024 the AI Engineering Portfolio Track — a longer program built around a real portfolio project, designed for learners who want to work independently with AI systems after completing it. All three courses remain online and self-paced, with the same emphasis on clarity and honest assessment that shaped the first one.
Mission
To give learners a clear, well-paced path into AI development — with materials that describe what is taught rather than what it might lead to.
Vision
A learning environment where progress is visible and the next step is always clear — where feedback is a normal part of the work, not an afterthought.
Values
Honesty in describing what a course covers. Respect for the learner's time and pace. Plain language over technical performance.
The Team
Small by choice. Every course is designed and taught by people who work with AI systems professionally.
Pawarit Kaewchan
Founder & Lead Instructor
Pawarit has been building data pipelines and ML models since 2016. He designed the curriculum for all three courses and leads the weekly Q&A sessions for the intermediate track.
Nattaya Ruangsuk
Course Designer & Reviewer
Nattaya writes the exercises and reviews submitted work for the beginner and intermediate courses. Her background is in data analysis and applied statistics.
Arjun Charoenwong
Portfolio Track Mentor
Arjun leads the AI Engineering Portfolio Track, running code reviews and mentor sessions. He has spent five years building and maintaining production AI services for regional tech companies.
How We Work
A few principles we hold to across every course and every learner interaction.
Accurate course descriptions
Each course page explains the prerequisites, the pace, the format, and what is included. We update descriptions when course content changes.
Human-reviewed exercises
Submitted work is read and responded to by a team member. Automated checks are used only for things like syntax errors, not for the substance of your work.
Data privacy
Learner data is stored securely and is not shared with third parties outside of essential services. You can read the full details in our Privacy Policy.
Materials kept current
Course notebooks, datasets, and reading notes are reviewed before each new cohort and updated where the underlying tools or methods have moved on.
Accessible support
Questions are answered by email and in the weekly session. We aim to respond to email queries within one working day during the Thai school year calendar.
Clear progress tracking
Learners on the Portfolio Track receive a written progress record. Each module is marked as complete only after a review, not just on submission.
AI education that stays grounded
The interest in AI development has grown considerably over the past few years, and with it the number of courses, videos, and platforms offering to teach it. Neuronest occupies a specific position in that landscape: structured, human-guided, and priced for individual learners in Thailand who are not studying through a university.
Our three courses cover the range from foundational programming and data handling through to deploying AI systems in a form other people can depend on. Each level assumes the previous one, which means a learner who completes all three has covered not just the concepts but the practical work of building, evaluating, and maintaining a model — and has a portfolio to show for it.
We are based in Chiang Mai because that is where the founders work and because the city has a growing community of practitioners across software engineering, data work, and related fields. Our courses are fully online, which means learners anywhere in Thailand — or elsewhere — can enrol and participate. But the Chiang Mai location matters to us: the weekly sessions happen in a timezone that makes sense for Southeast Asia, and the practical examples in the courses draw from the kinds of systems and problems that are common in the region.
If you are considering an AI course and want to talk through which level makes sense for where you are now, contact us. We will give you a straightforward answer.
Want to know more before enrolling?
Contact us with your background and questions. We will suggest the right starting point and explain what to expect from the course.
Contact Neuronest