Bangkok · Est. 2019

A school built around the idea that AI education should be honest and unhurried

rasmitez Tech was started by a small group of practitioners who had grown tired of the gap between what AI courses promised and what they actually delivered.

Our story

The school opened in Bangkok in 2019 with a single short course and a conviction that the most useful thing we could offer working professionals was not speed or credentials, but clarity. We wanted learners to finish our programmes with a sober, grounded understanding of what AI systems do, where they fall short, and what human judgment is still required to work with them responsibly.

We wrote the first curriculum ourselves, drawing on backgrounds in machine learning research, ethics, public policy, and organisational design. We kept the cohorts small from the start — partly because we knew that good written feedback takes time, and partly because we wanted the discussion threads in each week to feel like a real exchange rather than a broadcast.

Since then we have developed two further programmes: a practitioner track for those already working in applied AI who want to strengthen their evaluation and documentation practice, and a governance programme for people who support AI oversight work within wider organisations. The three programmes now form a loose sequence, though each is designed to stand on its own.

We are based in the Lumphini district of Bangkok and teach entirely online. Our learners have come from across Thailand, from Singapore, Japan, the Philippines, and further afield. The courses are taught in English.

In brief

Founded 2019 in Bangkok
Entirely online delivery
Courses taught in English
Small cohort model throughout
88 Witthayu Rd, Lumphini, Bangkok

"We think the most respectful thing a school can do is to be straightforward about what its courses will and will not give you."

— rasmitez Tech founding notes, 2019

These are the principles that shape how we build our courses and how we work with learners.

What we stand behind

Intellectual honesty

We describe what AI systems can and cannot do based on the current state of the field. We do not frame technical possibilities in a way that obscures their real limitations.

Pacing that respects work

All our programmes assume learners have jobs. The workload is meaningful but not punishing. We have designed the pacing so it can be sustained alongside full-time employment.

Writing as thinking

We use short written reflections as the primary learning method. Writing out what you understand — and where you are uncertain — produces clearer thinking than re-reading slides.

Small groups by principle

We limit cohort sizes so that each learner receives genuine written feedback from a tutor and so that discussion threads develop into real exchange rather than noise.

Care with personal data

We collect only the data we need to administer a place on a programme. We do not sell or share information for marketing purposes, and we are straightforward about what we hold.

Accountability to learners

If a programme is not working for a cohort member, we want to know early. We make it easy to raise concerns and we take them seriously when they arise.

The people who build and teach on our programmes come from research, policy, and applied engineering backgrounds. None of us believe the work of making AI responsible can be reduced to a single discipline.

The team

Priya Ratnasamy

Programme Director

Priya leads curriculum development and oversees the Governance Programme. Her background is in public policy and organisational design, with a focus on accountability frameworks for automated decision systems.

Kritchai Thongprasert

Lead Instructor — Responsible AI

Kritchai designed and teaches the Responsible AI Practitioner Track. He has worked in applied machine learning in Bangkok and Singapore, and writes about model evaluation and documentation practice.

Nattaya Lertprasertkul

Instructor — Ethics and Foundations

Nattaya teaches the AI Ethics and Foundations course and coordinates the weekly discussion threads. Her academic background is in applied ethics and philosophy of technology.

These are the standards and practices we hold ourselves to across all three of our programmes.

How we work

Written feedback on all work

Every written submission receives a tutor response with commentary, not just a score or a pass/fail indication.

Secure online environment

Learning materials, submissions, and discussion threads are hosted in a password-protected environment with encrypted data in transit and at rest.

Annual curriculum review

We review course content at the end of each cohort cycle and update it to reflect developments in the field and feedback from participants.

Privacy-first data practice

We collect and retain only the information required to administer your place on a programme, and we hold it in accordance with our published privacy policy.

AI education that starts from what is actually known

There is a considerable distance between the public conversation about artificial intelligence and the reality of what current AI systems do and do not do. Our programmes are built around closing that distance for people who work with or near AI in a professional context.

The AI Ethics and Foundations course is designed for learners who are encountering these questions for the first time and want a careful, structured way into them. It does not assume technical background, but it does assume that the learner wants to think seriously — about how fairness is defined and measured in AI systems, about the contexts in which automated decision-making is and is not appropriate, and about the practical responsibilities of people who commission, deploy, or evaluate AI tools.

The Responsible AI Practitioner Track takes those foundations and extends them into the specific practices of model evaluation and documentation. Participants work with structured assessment approaches, produce model cards and data sheets in a realistic format, and consider how to communicate technical findings to colleagues without machine learning backgrounds. The applied project in this track is drawn from a working context familiar to the participant.

The AI Governance Programme is the most substantial of the three. It is designed for people who support or lead governance work around AI systems within an organisation — not necessarily as technical specialists, but as the people responsible for ensuring that the organisation's use of AI is considered, documented, and subject to appropriate oversight. Participants work through assessment frameworks, draft policy text, and meet regularly one-to-one with a tutor throughout the five-month programme.

Ready to learn more, or have a question first?

We are glad to answer questions before you make a decision. Please write to us or call during office hours.