Experiences from people who have been through our programmes
Working professionals across Malaysia — career changers, developers, and domain specialists — on what the learning experience was actually like.
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Graduates
4.8
Average rating
18
Cohorts completed
3
Years running
What participants wrote
Zulaikha Ahmad
HR Manager · Petaling Jaya
"I joined the Foundations programme with no background in coding at all, which made me nervous. The first two weeks were genuinely difficult, but my mentor noticed I was struggling with the loop exercises and sent me a set of additional examples before the next clinic. That kind of attention is not something you get on most platforms."
Foundations of AI with Python · May 2025
Rajan Krishnamurthy
Software Developer · KL Sentral
"The Applied ML Engineering programme is genuinely different from what I had tried before. The three projects were not toy datasets — one of them was based on a logistics pricing scenario that my company would actually run into. The code review comments were detailed and occasionally uncomfortable, which is exactly what I needed."
Applied ML Engineering · April 2025
Lim Yee Ling
Data Analyst · George Town, Penang
"I liked the structure and the pace. The clinic format works well — you are not watching someone else's question get answered while yours gets lost. I would have appreciated slightly more time on evaluation metrics in the Foundations track, but the mentor pointed me toward the right follow-up material when I asked."
Foundations of AI with Python · May 2025
Farouk Osman
Operations Lead · Shah Alam
"The session on presenting findings to non-technical colleagues in the Applied ML programme was worth the programme fee on its own, honestly. I had been struggling to explain model outputs to my manager. The session gave me a framework I used at work within two weeks of the cohort ending."
Applied ML Engineering · March 2025
Priya Subramaniam
ML Engineer · Bangsar, KL
"Deep Learning and Neural Networks was exactly the kind of course I had been looking for — it does not skip the maths. Faiz's written feedback on my milestone submissions was detailed enough that I could track exactly where my understanding had a gap. The capstone project took the most time but it is the thing I am most glad I did."
Deep Learning and Neural Networks · April 2025
Nur Izzati Mohd
Secondary School Teacher · Johor Bahru
"I work full-time and have two children, so the flexibility of being able to watch lessons whenever I had a free hour was important to me. The six-to-eight hours per week estimate was about right. I finished the Foundations programme in eight weeks without feeling rushed, and now I understand what a model is actually doing — which I did not before."
Foundations of AI with Python · May 2025
How participants used what they learned
Razif Abdullah
Logistics Coordinator, Klang Valley · Applied ML Engineering graduate
Challenge
Razif's team was manually flagging shipments at risk of delay based on experience and gut feel. The process was inconsistent and time-consuming, and it was not catching all the delays. He enrolled in the Applied ML Engineering programme hoping to build something more systematic.
What he worked on
During the third project in the cohort — a logistics forecasting scenario — Razif adapted the exercise to use data closer to his actual work. His mentor's feedback helped him identify that he was using a feature that would not be available at prediction time, which forced him to rethink the pipeline design.
What followed
Three months after completing the programme, Razif had built a working prototype for his team. The model flagged around 70% of the eventual delays with reasonable precision — not a finished product, but enough to change how the team allocated checking time. He credits the code review sessions with giving him the structural habits to maintain the pipeline as it grew.
Jacinta Tan
Marketing Executive, Kuala Lumpur · Deep Learning graduate
Challenge
Jacinta wanted to move from a marketing role into a more technical position working with data and machine learning. She had taught herself some Python but found that her understanding of the underlying concepts was patchy — she could run the code but could not explain why it worked or debug it when it did not.
What she worked on
The Deep Learning programme's focus on the mathematics behind training was what Jacinta said she needed most. The capstone — a vision classification task using a small dataset of product images — took most of the final month, and the detailed feedback on each milestone helped her understand what the model was actually doing, not just what the output said.
What followed
Within five months of completing the programme, Jacinta had moved into a junior ML role at a retail tech company in KL. She credits the capstone project specifically — she showed the repository during her interview and was able to walk through the design decisions and trade-offs, which the panel said distinguished her from other candidates.
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Hours
Mon–Fri 9am–6pm
Sat 10am–2pm
Professional recognition
MDEC Community Learning Partner
Recognised by Malaysia Digital Economy Corporation for contributing to AI skills development, 2023.
UM Faculty Affiliate
Affiliate relationship with Universiti Malaya for curriculum feedback and mentor professional development.
Malaysia Digital Economy Awards
Shortlisted in the Digital Skills Development category, 2024.
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