Learner experiences at Suria Code

Learner voices

What it felt like from the inside

Notes from learners who went through the tracks — in their own words, with the details that actually helped them decide.

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4+

Years in Kuala Lumpur

340+

Learners across all tracks

4.7

Average satisfaction score

91%

Track completion rate

― What learners say ―

Feedback from recent cohorts

FA

Farah Anis

Marketing analyst · Petaling Jaya

I had tried two other online Python courses before this. Both left me lost after the first few weeks. Track 01 at Suria Code moved differently — the pace was slower, there was time to sit with things. The weekly clinic was what I kept coming back for. I asked basic questions and nobody made me feel odd about it. Finished the track in May and understood what I'd built, which hadn't happened before.

Track 01 · May 2025

ZR

Zulaikha Rahman

Software developer · KL

Track 02 suited where I was — I knew Python from work but hadn't done anything with data properly. The projects were the best part. Real data, real decisions, no hand-holding on the answers. Mentor feedback on my first project pointed out something I'd been doing wrong in my evaluation approach that I wouldn't have spotted alone. The eleven weeks felt right — not padded, not rushed.

Track 02 · April 2025

KW

Khairul Wan

Backend engineer · Shah Alam

Deep learning was something I'd read about for two years and never gotten into properly. Track 03 was the push I needed. The capstone took more time than I expected — the scope was genuinely demanding — but the guidance from the mentor team kept it from becoming overwhelming. I deployed my first model properly and understood what was happening at each layer. The alumni garden afterwards has been useful too.

Track 03 · May 2025

NM

Norzahra Mahat

Accountant · Ampang

I came in with no technical background at all. The beginning track was described to me as something for absolute starters and it genuinely was. Ruzaini explains things without assuming you already know the vocabulary, which made a difference. I won't pretend six weeks was enough to make me confident with everything, but I left with something working and a clear sense of what to do next.

Track 01 · April 2025

SH

Syafiq Hairul

Data entry supervisor · Cheras

Did Track 01 and Track 02 back to back across about six months. The second track built on the first in a way that felt deliberate — it wasn't just more content piled on, the tools connected. Siti's feedback on my second project was the most useful educational writing I've received in any course. She identified a pattern in my thinking that I've since noticed elsewhere in my work.

Track 01 + 02 · Mar–May 2025

RI

Rashidah Ibrahim

Research officer · Putrajaya

My manager suggested I look into machine learning for a research project we had coming. Track 02 was a natural fit. I appreciated that the fee covered everything — there was no moment where I needed to buy something extra or sign up for another platform. The peer channel was livelier than I expected; a few of us are still in touch after the cohort ended.

Track 02 · May 2025

― Learning journeys ―

Three learners, three paths

AS

Azhar Sulaiman — from logistics officer to data analyst

Track 01 → Track 02 · 2024–2025

The challenge

Azhar had ten years in logistics and recognised that his company's planning reports were based on spreadsheets that weren't scaling well. He wanted to understand whether machine learning could help, but had no programming background and needed something that didn't require quitting his job to study.

The path

Azhar completed Track 01 in late 2024 — evenings and weekends, with the clinics as his main touchpoint each week. He moved into Track 02 in early 2025, using delivery data his company shared with him (anonymised) as the basis for one of his project submissions.

What changed

By the end of Track 02, Azhar had built a demand forecasting model for a subset of his company's routes. It isn't in production — "we're working on that" — but it was enough for him to move into a hybrid data role at his company. He attributes much of the credibility to having something concrete to show.

"I told the hiring panel I'd completed the track and had a working model. That opened the conversation. I don't think I'd have had that without the project."
MY

Melissa Yong — a graphic designer who wanted to understand AI tools

Track 01 · April–May 2025

The challenge

Melissa was seeing more AI image and text tools in her design workflow and wanted to understand what was happening underneath. Not to become a developer, but to be able to speak more usefully with the developers her agency works with and to evaluate tools with more than intuition.

The path

She joined Track 01 with no prior coding experience. The beginning track moved slowly enough that she was able to keep up alongside a full working week. The capstone — a simple classifier trained on image category data — gave her something practical to reference in later conversations.

What changed

Melissa didn't switch careers, which she was clear she wasn't trying to do. But she describes the difference in how she approaches tool evaluation as meaningful — and she's now mid-way through Track 02 as of writing, having decided she wanted to go further than she originally planned.

"I came in with a narrow goal and left wanting to keep going. That's not what I expected when I signed up."

― Find us ―

Get in touch with the team

Address

Jalan Bukit Bintang 71
55100 Kuala Lumpur

Hours

Mon–Fri 9am–6pm
Sat 10am–2pm

― Credentials ―

Recognised and registered

MSC Malaysia Registered Training Provider

Recognised by MDeC under the MSC Malaysia initiative for technology training providers.

HRDCorp Claimable Provider

Programme fees claimable by eligible Malaysian employees via the HRDCorp levy scheme.

PDPA 2010 Compliant

All learner data handled in accordance with Malaysia's Personal Data Protection Act 2010.

― Add your own story ―

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