What Learners Say About Studying at Damai Labs
Honest reflections from working professionals in Malaysia who completed one or more of our tracks.
← Back to Home4.8
Average Rating / 5
180+
Learners Enrolled
91%
Track Completion Rate
3+
Years of Cohorts
From the Learners Themselves
Nurul Syahida
Data Analyst · Kuala Lumpur
I joined the AI Starter Course knowing nothing about Python — I work in data analysis but had always avoided the coding side. The pace was genuinely unhurried. By week three I had something running that I actually understood. The weekly clinic was where a lot of things clarified for me; I appreciated being able to bring accumulated questions rather than just hoping for them to come up in the session.
May 2025 · AI Starter Course
Raj Hari
Software Developer · Penang
The Machine Learning Track was the right level for me. I had dabbled with Python before but had no idea how to structure a proper data pipeline or evaluate a model meaningfully. Ahmad's feedback on my first project was specific and useful — not just corrections but actual observations about my reasoning. That kind of written response is hard to find.
April 2025 · Machine Learning Track
Lim Wei Ling
Research Engineer · Selangor
I completed the Deep Learning Sanctuary in early 2025 after doing the ML Track the previous year. The capstone was the hardest thing I have built — deploying a model via an API was something I had always found daunting. The cohort was small enough that you get actual attention from the instructor, which matters when you are debugging something that has three moving parts. The alumni space has stayed active, which I did not expect.
March 2025 · Deep Learning Sanctuary
Azri Zulkifli
Marketing Manager · Johor Bahru
My background is marketing, so joining an AI course felt like crossing into another world. But I needed to understand how data and models work to do my job better. The Starter Course did not assume anything. Siti was patient with questions that must have seemed basic. I finished with a working project and a much clearer sense of what AI tools can and cannot do.
May 2025 · AI Starter Course
Tan Kah Wai
Freelance Developer · Penang
I have tried two other ML courses before Damai Labs. The main difference is the size of the cohort. In the others I never asked a question because it felt like shouting into a room. Here there were maybe twelve of us, and you could actually have a back-and-forth. The peer channel between sessions was more useful than I expected — someone usually posted something relevant before the next session.
April 2025 · Machine Learning Track
Farah Musa
Finance Analyst · Kuala Lumpur
The pricing in Ringgit was one reason I chose Damai Labs — most comparable courses are priced in USD and the cost becomes significant. The content itself was solid. My one suggestion would be slightly more time on the pandas section at the start of the ML Track, but that is a minor point. The recordings meant I could review it at my own pace anyway.
May 2025 · Machine Learning Track
Three Paths Through the Curriculum
Nurul Syahida — Data Analyst to AI Practitioner
AI Starter Course · 6 weeks · RM 980
Challenge
Working in data analysis for several years but unable to use Python or build predictive models independently. Relied entirely on Excel and vendor tools.
Process
Joined the AI Starter Course. Used the weekly clinic heavily in weeks two and three. Completed a classification project on a publicly available dataset by week six.
Outcome
Now maintains a small internal Python script that pre-processes monthly reporting data at her company. Enrolled in the ML Track for the next cohort.
Raj Hari — Software Developer Adding ML Skills
Machine Learning Track · 11 weeks · RM 1,400
Challenge
Comfortable with Python and backend development but had no structured understanding of how to build or evaluate ML models for client projects.
Process
Completed the ML Track over 11 weeks, submitting two projects — a regression task and a classification pipeline. Received detailed feedback on both.
Outcome
Used both completed projects as portfolio pieces when pitching for a data engineering contract in Penang. The contract was won. He credits the project feedback for tightening the quality of his work.
Lim Wei Ling — ML to Deep Learning in Two Cohorts
ML Track + Deep Learning Sanctuary · 24 weeks total
Challenge
As a research engineer, needed to understand neural networks at implementation level, not just conceptually. Previous courses had been theoretical without enough hands-on depth.
Process
Completed ML Track in late 2024, then joined the Deep Learning Sanctuary cohort in early 2025. Capstone involved training and deploying a text classification model.
Outcome
The deployed capstone is now used internally at her research institution as a document categorisation tool. She continues to access the alumni channel for questions on newer model architectures.
Reach Out Directly
Address
Jalan Burma 153
George Town, Penang
Office Hours
Mon–Fri: 10–18
Sat: 10–14
Professional Recognition
MSC Malaysia–Aligned Curriculum
Developed in alignment with Malaysia's national digital economy education priorities.
PyTorch Community Recognition
Recognised by the PyTorch community as an independent educator for curriculum quality in applied deep learning.
PDPA Compliant Operations
Learner data managed in accordance with Malaysia's Personal Data Protection Act 2010.
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