A school shaped around
the people who attend it.
Mentari Labs was built in Kuala Lumpur by practitioners who wanted to make AI education approachable for working adults — without shortcuts or hype.
Back to HomeHow Mentari Labs came together
Mentari Labs grew out of a recurring observation: a lot of smart, motivated people in Malaysia were keen to build with AI, but the courses available to them were either too fast-paced for someone holding down a job, or too shallow to produce any real competence. The result was frustration — not with the learners, but with how the material was being delivered.
A small group of practitioners — engineers, data scientists, and educators — started meeting informally in Bangsar to try a different approach. They ran pilot workshops where the pace was set by the slowest question in the room, not by a fixed lecture schedule. Participants left feeling capable rather than overwhelmed. That became the model.
Mentari Labs was formally established in 2022. The name references the sun — mentari is Malay for sunlight — and the idea that learning should feel illuminating rather than pressured. Today the school operates entirely online, serving cohorts of working professionals who want to move steadily through AI fundamentals and applied work, at a pace that respects the rest of their lives.
What drives what we do
Make progress feel steady
Every syllabus is structured so the step from one week to the next is manageable. We do not skip foundations to reach the exciting parts faster.
Keep mentoring personal
Small cohorts mean that feedback addresses your specific code and your specific confusion, not a generalised answer to the average learner's question.
Connect to the local market
We draw on Malaysian industry cases so that what you learn has immediate relevance to the employers and sectors around you.
Teach responsibility alongside technique
AI work has real consequences. We include responsible deployment and ethical considerations in every track, not as an afterthought.
The instructors and mentors at Mentari Labs
Everyone who teaches here works — or has recently worked — in the field. That keeps the material grounded in what actually matters day-to-day.
Ahmad Rasyid
Lead Instructor, ML
Former data scientist at a KL-based fintech, Ahmad leads the Applied Machine Learning track and mentors across all cohorts. He focuses on keeping examples close to real-world data problems.
Nurul Farhana
Deep Learning Instructor
Nurul holds an MSc in computer vision and spent four years in research before joining Mentari Labs. She leads the Deep Learning Voyage and brings particular care to the capstone guidance process.
Lee Wei Jian
Python Foundations Mentor
Wei Jian started as a self-taught developer and transitioned to data engineering over three years. He mentors the Starter track and has a particular talent for explaining why things work, not just how.
Standards we hold ourselves to
Curriculum review each cohort
After every cohort we review feedback and update examples to reflect changes in tooling and industry practice. Nothing stagnates for more than one cycle.
Learner data protection
Enrolment and payment data are handled in line with Malaysia's Personal Data Protection Act 2010. We do not share personal information with third parties for marketing.
Capped cohort sizes
We limit each cohort to maintain the mentor-to-learner ratio that makes personalised feedback possible. When a cohort is full, we open a waitlist for the next one.
Ethics woven into the curriculum
Responsible AI practices are not a standalone module — they appear throughout every track, because good engineering habits are easier to build early than to retrofit.
Portfolio-verified completion
Certificates are awarded on completion of coursework and a portfolio project, not just attendance. Employers can verify completion through our website.
Support that responds
Enquiries and support requests receive a response within one business day. During active cohorts, the peer channel is monitored by staff throughout the week.
AI education for working adults in Malaysia
The demand for AI and data skills across Malaysia has grown steadily as companies in sectors from logistics to healthcare to financial services start to examine how machine learning and automation can fit into their work. But many of the people positioned to fill those roles — experienced analysts, software developers, product managers — are already fully employed. Their challenge is not motivation; it is finding a learning format that fits alongside a 45-hour work week.
Mentari Labs addresses this by structuring every programme around the reality of a busy adult schedule. Lessons are pre-recorded and can be watched in segments. The live weekly clinic is the only fixed time commitment, and it is kept to ninety minutes. Project deadlines are firm enough to maintain momentum but spaced to allow genuine work rather than rushed submissions.
Our instructors bring recent, hands-on experience. The Python and machine learning curriculum is built around tools that Malaysian employers are actively using — pandas, scikit-learn, PyTorch — and the examples are drawn from sectors that are hiring here. When a learner completes a track at Mentari Labs, they leave with a portfolio project they can walk through in an interview, a working understanding of how the tools behave on messy real data, and a habit of thinking clearly about what a model is actually doing and why.
The name Mentari was chosen deliberately. We wanted something that felt like the beginning of a day rather than the middle of a storm. Learning AI should feel like clarity arriving, not pressure accumulating. That intention shapes how we write our materials, how our instructors give feedback, and how we handle the inevitable moments when a learner gets stuck on something that seemed simple.
Want to know more about how we work?
Send us a message and we will walk you through the options. There is no obligation to enrol until you are certain it is the right fit.
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