Our story
We believe learning AI should feel possible
Khwamru was built around a simple idea: that understanding artificial intelligence shouldn't require rushing, confusion, or a computer science degree from day one.
Back to HomeWho we are
A small school with a clear purpose
Khwamru opened in Bangkok with the aim of making AI development education more approachable for people already working in technical fields — engineers, analysts, and developers who wanted to add machine learning to their skills without leaving their jobs to do it.
The name "Khwamru" (ความรู้) means knowledge in Thai — a reflection of our belief that learning should be steady, cumulative, and worth the effort. We write our courses with care, test them with real learners, and revise them based on what actually helps people progress.
We are not a large platform with hundreds of courses. We focus on three carefully developed programmes in machine learning, deep learning, and model deployment — and we work to make each one genuinely useful.
Our mission
To provide clear, practical AI education that working professionals in Thailand can follow at their own pace, without unnecessary complexity or pressure.
Our approach
We write each lesson with the learner's experience in mind — short enough to complete in an hour, clear enough to understand without re-reading several times, and practical enough that the next step always feels within reach.
Our values
Patience, honesty, and thoroughness. We don't cut corners in our course design, and we don't oversell what AI can do. We'd rather give you a realistic picture and the skills to work within it.
The people behind it
Our team
A small group of practitioners and educators who have worked with machine learning in real settings and enjoy explaining what they know.
Pracha Worawich
Founder & Lead Instructor
Pracha has worked in data science for over eight years across finance and logistics. He started Khwamru after spending several years running informal study groups in Bangkok.
Naphat Srisawat
Deep Learning Instructor
Naphat focuses on neural network architectures and computer vision. She enjoys breaking down concepts that look complicated into steps that feel manageable.
Kanokwan Thongchai
MLOps & Deployment Specialist
Kanokwan has helped engineering teams in Bangkok and Singapore move models from notebooks into reliable production systems. She leads the deployment and MLOps curriculum.
How we work
Standards we hold ourselves to
Every course we publish goes through a careful review process before learners see it. These are the areas we pay particular attention to.
Content accuracy
Every technical explanation is reviewed by at least one practitioner before publication, and we revise course material when libraries or tools change.
Learner testing
Before a new course goes live, we run it with a small group of learners who match the intended audience. Their feedback shapes the final version.
Privacy and data care
We handle learner data carefully and do not share it with third parties for marketing purposes. Your course progress and personal details stay with us.
Working code throughout
All code examples in our courses are tested to run on standard environments. We include setup guides so you're not left guessing about configuration.
Instructor availability
Questions submitted during a course are answered within one working day. We take support seriously and don't leave learners waiting for days.
Regular updates
AI tools and frameworks change frequently. We schedule reviews of all course content every six months to keep the material current and relevant.
AI education built for working professionals in Thailand
Khwamru sits in the Watthana district of Bangkok, a few minutes from Ekkamai BTS station. We run all three of our programmes entirely online, which means the courses are accessible to learners across Thailand — from Chiang Mai to Phuket — as well as to Thai professionals working abroad.
Our machine learning foundation course covers the core statistical and algorithmic ideas that underpin modern AI systems. Learners work through regression, classification, and clustering methods using Python and standard scientific libraries. The course is written without assuming familiarity with university-level mathematics, though comfort with basic arithmetic and some programming experience does help.
The applied deep learning programme focuses on neural networks through a project-based structure. Learners build image classifiers, text processors, and time series models across the course — each project is scoped to be achievable within a few hours, so progress accumulates without becoming overwhelming. We use PyTorch as the primary framework.
The model deployment and MLOps course addresses one of the most practically important and least often taught parts of the AI development lifecycle: what happens after you've trained a model. Topics include containerisation, serving infrastructure, monitoring, and the process of coordinating machine learning work within a software engineering team.
All three courses are offered in English and priced in Thai Baht. We accept payment by bank transfer and can provide documentation for professional development expense claims.
Have a question about our school?
We're happy to talk about which course might suit your background and what to expect from the learning experience.
Get in Touch