From the People Who Have Been Through It
What learners noticed, what surprised them, and what changed after their time at Ilmu Nexus.
Back to Home280+
Learners across all cohorts
4.8
Average satisfaction rating
94%
Programme completion rate
3
Years running community programmes
What Learners Say
Farhana Ahmad
Petaling Jaya · First Steps
"I had zero coding background and was nervous about starting. The pace in the first few weeks was comfortable — nobody made me feel slow for asking basic questions. By week five I had written a working model, which I genuinely did not expect. The peer group became a real support network."
May 2025
Rajan Krishnan
Kuala Lumpur · ML Cohort
"The eleven weeks were a lot of work, I won't pretend otherwise. But the group review sessions were the best part — hearing how others approached the same problem taught me more than any lecture. I wish the live session times were more flexible, though recordings helped. Would still recommend."
April 2025
Nur Izzati Razak
Shah Alam · First Steps
"What I appreciated most was that exercises used datasets that actually made sense to me — local transport data, market data. It stopped feeling like I was learning in a vacuum. The mentor clinics were small enough that I could actually ask follow-up questions without feeling like I was wasting anyone's time."
May 2025
Zaharudin Hassan
Subang Jaya · Deep Learning
"I had done online ML courses before but always felt like I was studying alone. The Deep Learning Builders cohort was genuinely different — the small group size meant the mentor knew where each of us was struggling. My capstone got two rounds of detailed feedback before I submitted it. The alumni space still gets used regularly."
April 2025
Priya Letchumanan
Klang · ML Cohort
"I joined as a career changer from accounting, and the programme met me where I was. There were moments when the pace picked up and I had to rely on recordings to catch up, which worked fine. The project felt personally meaningful because we could choose a domain we understood. Good value for what was included."
May 2025
Adam Marzuki
Kuala Lumpur · Deep Learning
"The deployment section in weeks ten and eleven was the part I had been most nervous about, and it ended up being the most useful. Having a mentor walk through the real considerations — not just the theoretical ones — made a noticeable difference. The programme's pricing is competitive for what you actually get."
April 2025
Three Learner Journeys in Detail
Siti Yusof — Career Change from HR
First Steps · Practical ML Cohort · Kuala Lumpur
The Challenge
Siti had been working in HR for six years and wanted to move into people analytics, but had no technical background. She had tried self-study through free online materials and stalled repeatedly at data manipulation tasks with no one to ask.
What Helped
She joined First Steps and completed it over seven weeks, then moved into the ML Cohort the following intake. The peer courtyard gave her a place to ask questions she had been embarrassed to post publicly. Her capstone used HR attrition data she understood well.
The Outcome
By the end of the ML Cohort, Siti was handling data pipelines independently and had a documented project to show. She moved into a people analytics role within four months of completing the second programme.
"The kampung feel is real — I always had someone to turn to when I got stuck, and that made the difference between giving up and finishing."
Daniel Tan — Software Developer Upskilling
Deep Learning Builders · Petaling Jaya
The Challenge
Daniel had three years of Python experience and had tinkered with ML through tutorials, but felt he lacked the depth to speak confidently about model design decisions. He wanted structured guidance, not more self-directed material.
What Helped
He joined the Deep Learning Builders Programme directly. The mentor's background in production ML meant feedback on his capstone went beyond syntax — it covered real deployment trade-offs. The small cohort meant he could have conversations rather than just watch.
The Outcome
Daniel finished with a transformer-based text classification system as his capstone. He continues to use the alumni courtyard to share progress on a side project, and says the mentor feedback during the programme changed how he thinks about model evaluation.
"I stopped treating ML as a black box after this programme. That shift in confidence has been worth more than any specific skill."
Hafizuddin Borhan — Fresh Graduate
First Steps → ML Cohort · Cyberjaya
The Challenge
Hafizuddin graduated in business administration and wanted to get into data-related work, but job descriptions kept asking for Python and ML skills he did not have. He was unsure whether he could learn it given his non-technical degree.
What Helped
First Steps removed the uncertainty about whether he could code. Using a retail dataset for his capstone project felt natural given his business background. He enrolled in the ML Cohort the following month and found the community already familiar.
The Outcome
Six months after starting First Steps, Hafizuddin had completed two programmes and had two documented projects. He credits the clear progression between programmes for keeping him on track and not drifting between random courses.
"The path from one programme to the next was clear. That structure kept me moving forward instead of feeling lost between things."
Get in Touch
Have a question about our programmes? We're happy to help.
Phone
+60 16-738 4925Address
Jalan Sultan Ismail 96
50250 KL
Hours
Mon–Fri: 9am–7pm
Sat: 9am–2pm
Ready to Write Your Own Story?
Send us a message and we will help you find the right programme for where you are starting from.
Get in Touch