About Bestari Tech
Teaching AI work the way a studio would
We started with the view that most AI courses are built for speed. We built ours for depth.
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How Bestari Tech began
Bestari Tech grew out of a frustration shared by a small group of people working in data and AI in Kuala Lumpur. The courses available at the time were either introductory videos that stopped short of real work, or intensive programmes that moved so quickly that the ideas never had time to settle.
We opened in 2022 with a single cohort of nine students and one teacher. The format was simple: a defined scope of work, structured written feedback on each submission, and enough time to think before moving on. By the end of that first intake, something had clicked — not just in the students' code, but in the way they talked about the problems they were solving.
Since then we've run twelve intakes across our three course levels. The studio has remained deliberately small. We add a new cohort only when a teacher with the right experience is available to lead it. The result is a school that operates more like a workshop than a platform.
Mission
"To offer AI development study that rewards careful work rather than rapid completion — structured around projects, teachers, and written exchange."
Studio Numbers
The Teachers
People who do the work they teach
Each teacher at Bestari Tech has an active practice in AI or data engineering. They write the course materials themselves, from the work they do week to week.
Reza Azman
Lead Teacher — Studio Foundations
Reza has worked in data engineering in Kuala Lumpur for eight years. He designed Studio Foundations after noticing that most entry-level courses skipped the part where you actually structure a project from scratch.
Nurul Izzah
Lead Teacher — Studio Practice
Nurul leads the Studio Practice course, drawing on her background in applied machine learning at a fintech firm based in KL. She is particularly interested in model evaluation and what it means to know when a model is actually working.
Shaiful Karim
Senior Teacher — Long-form Programme
Shaiful oversees the Long-form Studio Programme, bringing twelve years of experience across model deployment, data infrastructure, and portfolio-level project work. He leads all final portfolio reviews.
Standards
How we keep the teaching honest
These are the practices we hold ourselves to, not aspirations printed in a brochure.
Written Feedback on Every Submission
No automated scoring. A teacher reads each submission and writes a response. This is built into the course structure and cannot be scaled away.
Cohort Size Cap of 16
Each intake is capped so that feedback stays specific and useful. We open a new cohort only when a teacher has the capacity to run it properly.
Projects, Not Just Exercises
Coursework is structured around small, complete projects with a defined aim and a real deliverable — not isolated exercises that don't connect to each other.
Data Privacy in Teaching
Student work is kept private. We do not share submissions publicly, use learner data for marketing, or retain personal data beyond the period required for course administration.
Curriculum Written by Practitioners
Course materials are written by the teachers themselves from their own working experience, reviewed each intake, and updated when the field moves in a direction that matters.
End-of-Course Review
At the end of each intake, every student is invited to give written feedback on the course. We read it, respond to it, and use it to adjust the next run.
Our Approach
AI development education that respects the difficulty of the work
The field of AI development has a great deal of accessible material — videos, articles, notebooks, open datasets. What is harder to find is structured study that takes a learner from general curiosity through to the kind of careful, considered practice that produces work they can stand behind.
Bestari Tech was built to fill that gap, specifically for learners in Malaysia who are working in English and want a school that operates in their time zone and at a pace that doesn't assume everyone is racing toward a job offer. Our students include working professionals who are adding AI capabilities to an existing career, and people making a considered shift into data-related work after time in other fields.
The studio format — small cohorts, teacher-led written feedback, project-based assessment — draws from a longer tradition of craft education that has nothing to do with technology. Good teaching is largely the same across fields: you read someone's work, you think carefully about where it is strong and where it is not, and you write something honest and useful back to them. That's what we try to do.
We are based at Menara Maxis in KLCC, and all sessions run in Malaysian time. Students join from across peninsular Malaysia and from East Malaysia, and occasionally from the region. The courses are online but not asynchronous in spirit — there is a teacher at the other end, and that teacher is paying attention.
Begin
Ready to start a careful first season of study?
Write to us with a little about where you are. We'll suggest the right course and let you know when the next intake opens.
Get in Touch