What people say when they have finished the work.
Feedback from working professionals in Malaysia who have completed programmes at Kelip Akademi. Unedited except for minor formatting.
← Back to HomeFrom learners across three programmes
Zulfadli Azman
Data Engineer · Penang
I joined the full pathway after about two years of writing Python for pipeline work but with no real exposure to the ML side. The first three modules covered ground I thought I knew but turned out to have gaps in — particularly around feature engineering. The capstone took longer than I expected but that was mostly on me for underestimating the deployment section.
Full AI Pathway · June 2025
Priya Krishnamurthy
Product Manager · George Town
The Weekend Foundations course was three weekends of fairly dense material. I am not a programmer and I was worried it would tip into code too quickly, but the statistical focus stayed consistent. I came away understanding correlation and sampling in a way that actually changes how I read the reports my team produces. Worth the RM 130, easily.
Weekend Foundations · July 2025
Nur Aisyah Ramli
ML Engineer · Kuala Lumpur
I had trained models at work for about eighteen months but everything we built stayed in notebooks or got handed off to someone else to deploy. The deployment module fixed that. Eight weeks, one project. By the end I had a running endpoint with drift monitoring on a cloud instance I set up myself. The live session each week was useful — real-time answers rather than forum posts.
Deployment Module · May 2025
Tan Hui Xian
Software Developer · Penang
The cohort model works better than I thought it would. Being with a group of people on the same week of the same module meant questions in the discussion channel were almost always relevant to what I was working on at that moment. The feedback on my week four submission was specific enough that I went back and redid parts of week two — which I would not have done without it.
Full AI Pathway · April 2025
Mohammad Syafiq
Business Analyst · Butterworth
I did the foundations course first mainly to check whether I could keep up with the material before paying for the full pathway. Turned out I could, and I enrolled in the next cohort intake about two months later. The foundations course is genuinely standalone — it helped at work even without going further.
Weekend Foundations then Full Pathway · June 2025
Loh Yee Ling
Research Scientist · Penang
Coming from an academic background, the thing that struck me most was how practical the material stayed throughout. The capstone is designed to replicate the kind of brief you would get at work, not a research paper. I had to write handover documentation as part of the final submission, which is not the kind of thing most academic programmes would ask for. Genuinely useful.
Full AI Pathway · July 2025
Three learner journeys in more detail
Zulfadli — from pipeline work to ML
Full AI Pathway · 24 weeks · June 2025
CHALLENGE
Zulfadli had been writing data engineering code for two years. He could move data reliably but had no structured exposure to model training, evaluation or the production side of ML.
PROGRAMME
The full 24-week pathway, taken in sequence from data handling through to the supervised capstone. He paused between modules four and five for three weeks due to a project deadline at work.
RESULT
Completed the capstone with a demand-forecasting endpoint for a simulated manufacturing dataset. The skills transferred directly to a project he was assigned at work within two months of finishing.
"The pause policy was the thing that made the difference for me. If I had had to choose between finishing the course and delivering at work, I would have dropped the course. Being able to pause meant I didn't have to choose."
Nur Aisyah — notebook to production endpoint
Deployment Module · 8 weeks · May 2025
CHALLENGE
Trained models regularly as part of her role but had never been responsible for taking one to production. All deployment work was handled by a separate team and she had no visibility into what that involved.
PROGRAMME
The eight-week deployment module. She used a sentiment classification model she had already trained as her starting point rather than the default module project.
RESULT
Completed the module with her own model running in a container on GCP, with a basic monitoring setup in place. She estimates the monitoring section saved her team from a silent drift problem about six weeks after the module ended.
"The live session each week was the part I underestimated. I expected it to be a lecture. It was mostly questions from the cohort, which meant by week three it was covering exactly the problems we were all hitting."
Mohammad Syafiq — foundations as a test of fit
Weekend Foundations then Full Pathway · June 2025
CHALLENGE
Wanted to move toward a more technical role but was uncertain whether structured AI study would be a good fit at this stage of his career. Reluctant to commit time and money to a 24-week programme without more information.
PROGRAMME
Started with the Weekend Foundations course over three weekends. Enrolled in the full pathway in the next available cohort approximately two months later.
RESULT
Currently in week nineteen of the full pathway. The statistics vocabulary from the foundations course made the ML evaluation weeks significantly more straightforward than he had anticipated.
"The foundations course at RM 130 is genuinely designed as a complete thing in itself. I could have stopped there and still used it at work. The fact that it also prepared me for the pathway was a bonus."
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