What people who have taken our courses say
Feedback from working professionals across Malaysia who have completed Cendekia courses.
Back to HomeFrom recent cohorts
Ruzaini Hamdan
Software Developer · Petaling Jaya
"I took the Applied Python course after a few years working primarily as a backend developer. The course did what it said — it focused on the patterns that matter rather than covering the whole language again. The weekly deliverables format meant I always knew where I stood. I found the PyTorch section harder than expected, and the feedback on my final project helped me understand where the gaps were. Worth the time."
April 2025 cohort
Nurul Zahirah
Data Analyst · Kuala Lumpur
"The research reading short course was two weeks well spent. I have been working in data for four years and knew what machine learning was in broad terms, but I kept running into papers I couldn't follow properly. The approach here — one paper per session, walking through each part together — was exactly what I needed. The reading framework we finished with is something I have used several times since."
March 2025 cohort
Ahmad Mustafa
Systems Engineer · Shah Alam
"I enrolled in ML Foundations expecting to be overwhelmed by the maths, but the pace of the early weeks was more manageable than I had anticipated. The linear algebra refresher was genuinely useful — I had studied it years ago and needed the context reset. The office hours made a difference; I submitted a question in advance one week when the live time didn't work, and received a proper written answer. I felt like someone was actually paying attention."
February 2025 cohort
Lee Wei Xian
Product Manager · Bangsar South
"I am not a developer and was uncertain whether the research reading course was pitched at someone like me. I asked before enrolling and got an honest answer: it would be fine for my purposes, which was to understand what the papers in my field were actually saying. That turned out to be true. The sessions were careful and unhurried. I have recommended this to two colleagues since."
April 2025 cohort
Suraya Binti Osman
Research Associate · Cyberjaya
"I completed both the ML Foundations course and the Applied Python course, which I think is the intended path. The Foundations course did prepare me better for the Applied Python content — particularly the parts on loss functions and model training, which came up again in the PyTorch weeks. My one note is that twelve weeks is a real commitment alongside a full-time role. That is stated clearly upfront, but worth taking seriously before you enrol."
January & March 2025 cohorts
Krishnamurthy Ponniah
Senior Developer · Subang Jaya
"I had been putting off doing something structured with Python for AI work for about two years. The Applied Python course was the right size — eight weeks is enough to make real progress without feeling impossible. The notebook and script section was the most useful for me professionally. Pricing in MYR made the decision easier than most overseas options I had been looking at."
March 2025 cohort
How learners have used what they studied
From infrastructure engineer to ML practitioner
Farid had spent eight years managing cloud infrastructure and wanted to move toward ML engineering. He understood the tooling at a deployment level but had no foundation in what the models were doing or why they behaved as they did. He was hesitant to take a full university programme given his workload.
He took ML Foundations first, then Applied Python in the following cohort. The twelve-week structure of the Foundations course was demanding alongside his role, but the recorded sessions helped him manage weeks that were more constrained. By the Applied Python course he had enough conceptual grounding to focus on the code rather than the theory.
By the end of the Applied Python course, Farid had built a working data pipeline and a simple classification model that he later used in a proof-of-concept at his workplace. He describes the courses as having given him a vocabulary and foundation that made self-directed learning afterward significantly easier.
"I would not have known where to start on my own. The structure meant I was never completely lost, and the feedback on my projects told me where I actually needed to do more work."
Following primary research independently
Mei Lin worked as a science writer and was covering developments in AI for a technology publication. She found herself increasingly reliant on secondary summaries and announcements, unable to evaluate primary papers on her own. She wanted to change that without committing to a long technical course.
She took the two-week research reading short course. The sessions were slower than she had expected — she had assumed the course would cover more papers — but found the depth of attention on each one was what she actually needed. The framework for reading claims and limitations was directly applicable to her work.
Within two months, Mei Lin had read four papers independently using the method from the course. She described feeling more confident engaging with authors and researchers in her field, and less dependent on others to interpret technical content for her. She noted the two-week format was accessible to someone in a demanding editorial role.
"Two weeks felt almost too short, but the method itself is the deliverable. I have used it far more times since than I did during the course."
Some numbers from four years of running courses
Professionals enrolled across all cohorts
Average rating from post-cohort feedback surveys
Rated assessment feedback as useful or very useful
Instructors with 7+ years of professional field experience
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