About Us
How Cendana Labs Came to Be
Cendana Labs grew out of a concern that most AI education had become too surface-level. Courses moved fast, covered many tools, and left learners who could follow a tutorial but struggled to adapt when something didn't fit the template. The people behind Cendana Labs — practitioners who had worked in data and software development across Malaysia and the region — wanted to try a different approach.
The school opened its first cohort in early 2023, running a small group through a six-week Python and AI fundamentals programme from a space in Damansara Damai. The pace was deliberate. Each session covered one thing thoroughly rather than three things lightly. Participants were encouraged to ask until they understood, not just until they could repeat the steps. That cohort produced learners who could actually reason about what they had built.
Since then, Cendana Labs has run multiple cohorts across its three tracks, refining materials after each round based on what participants found unclear or where they stalled. The school has stayed small by choice. Every enrolled learner gets attention from an instructor — not just access to a platform. That constraint shapes how many cohorts run each term and how the programme is structured.
The name comes from the cendana tree, a plant known in Southeast Asia for being slow to reach maturity but highly valued for its density. It felt like the right metaphor for the kind of learning we were trying to build.
Mission
To provide structured AI education where every step is solid before the next begins — and where learners leave with understanding, not just output.
Approach
Small cohorts, personal feedback, and a pace set by comprehension rather than a fixed schedule. Recordings included. No one left behind on a concept.
Values
Honesty about what takes time to learn. Respect for learners who hold jobs while studying. Care in how materials are designed and how feedback is given.
The Team
Instructors and Staff
A small group of practitioners who've spent time doing the work, then chose to teach it carefully.
Ahmad Hisyam
Lead Instructor
Worked in data engineering and ML systems for eight years before joining Cendana Labs to develop the foundational and machine learning tracks.
Nur Farhana
Deep Learning Instructor
Research background in computer vision and neural network training. Designs and runs the Deep Learning Foundry track and mentors capstone projects.
Roshan Kumar
Programme Coordinator
Handles scheduling, cohort logistics, and learner support. First point of contact for enrolment questions and programme guidance.
Our Standards
How We Keep Programmes Reliable
Materials Reviewed Each Cohort
After every cohort, instructors identify sections where participants stalled and update the material before the next run.
Instructor-Reviewed Projects
All project submissions are reviewed by a qualified instructor, not auto-graded. Feedback is specific and written.
Data Privacy Compliance
Learner data is handled in accordance with Malaysia's Personal Data Protection Act 2010 (PDPA). We do not share participant data for marketing.
Cohort Size Limits
Each cohort is capped so every participant can receive attention in sessions. Waiting lists are maintained rather than expanding cohorts beyond capacity.
Lasting Access to Materials
Participants retain access to session recordings and reading materials after the track ends, with no expiry date imposed.
Transparent Communication
Schedules, changes, and feedback are communicated promptly. Participants are not left to guess about programme logistics.
AI Development Education in Malaysia
The demand for AI and machine learning skills across Malaysia has grown considerably as companies in financial services, logistics, e-commerce, and healthcare invest in data-driven tools. Yet finding structured, well-paced training — rather than self-directed video libraries or intensive bootcamps — has remained difficult for working professionals who need something that fits around employment.
Cendana Labs sits in that space. The school focuses on AI development skills: Python for data work, machine learning model building and evaluation, and deep learning architectures with deployment. Courses are built around comprehension rather than coverage, and each programme is run by instructors with applied experience rather than academic distance from the subject.
The school operates from Kuala Lumpur and serves participants across Malaysia and neighbouring countries who attend the online sessions scheduled in Malaysian time. The fee structure is set in Ringgit, and support is available during Malaysian business hours.
For anyone considering whether to start with AI Foundations, move directly to the Machine Learning Track, or prepare for the Deep Learning Foundry, a conversation with the team is the simplest way to find the right entry point. There is no pressure to enrol in the first exchange.
Take the Next Step
Talk to Us Before You Decide
We're happy to answer questions about any track — what it covers, how the sessions run, and whether your current background is a good fit.
Contact the Team