CerdikCode
Cerdik Code learning environment

Our Story

Thoughtful AI Education, Built for Malaysian Learners

Cerdik Code was founded on a simple observation: most AI courses overwhelm before they educate. We chose a different path.

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Our Background

How Cerdik Code Came Together

Cerdik Code started in Penang in early 2023, when a small group of software developers and educators decided that the existing options for learning AI in Malaysia did not quite fit the people they knew. The online programmes imported from abroad moved quickly and assumed background knowledge that most local learners simply did not have. The local alternatives were often either too informal to be useful or too focused on credentials to be practical.

The name "Cerdik" comes from the Malay word for clever or quick-witted — and the intention behind it was deliberate. We wanted to build programmes that made people genuinely capable, not just certificated. So we started with the question of what a thoughtful, patient mentor would do with a student who had never touched Python, and we worked outward from there.

Today, Cerdik Code runs three structured tracks covering AI literacy, machine learning practice, and advanced deep learning. All are delivered online, with cohorts small enough that every student receives personal feedback on their work. Our mentors are active practitioners — people who use these tools in their own work and can speak honestly about what matters and what does not.

We are based at Lebuh Light in George Town and work with students across Peninsular Malaysia and East Malaysia. The pace of our programmes is deliberate. We would rather a student finish with solid, transferable understanding than race to a badge and forget what they learned two months later.

What We Stand For

Mission and Values

Clarity Over Speed

We design every programme to be understood, not just completed. A slower pace that builds genuine understanding is worth more than a fast track that leaves gaps.

Honest Mentoring

Our mentors give real feedback — not just encouragement. When something is not working, we say so clearly and help students find a better path forward.

Responsible Practice

We teach the limits and responsibilities of AI alongside the technical skills. Understanding what these tools cannot do is as important as knowing what they can.

The People

Who Teaches Here

Our mentors are working practitioners who have chosen to spend part of their time teaching. They bring current, honest experience into the classroom.

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Ahmad Zulkifli

Lead Mentor — ML Practitioner

A data scientist with eight years building predictive models in the logistics sector. Ahmad leads the Machine Learning Practitioner track and reviews every project submission personally.

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Nurul Rahmah

Curriculum Lead — Beginner Track

Nurul spent four years teaching computing at a secondary school before moving into edtech design. She wrote the AI Literacy curriculum and runs the weekly group sessions for beginners.

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Shen Cheng

Senior Mentor — Deep Learning Studio

A computer vision engineer who has deployed production models for manufacturing clients across Southeast Asia. Shen leads the advanced track and mentors capstone projects one-on-one.

Our Standards

How We Keep Quality Consistent

These practices shape every cohort we run — not as policies, but as habits we have maintained since the first intake.

Written Project Reviews

Every project receives a written response from the mentor — noting what works, what needs attention, and why. Automated scoring is not used.

Student Data Privacy

Personal data, submission content, and communications are handled with care. We do not share student information with third parties, and access is restricted to the teaching team.

Cohort Size Discipline

We cap every cohort at 12 students and do not extend this for demand. When a cohort is full, the next intake opens on a set date.

Curriculum Review Cycle

Each track undergoes a review between cohorts. Mentors flag outdated tools or changed practices, and the materials are updated before the next intake begins.

End-of-Cohort Feedback

Students complete a structured review at the end of each track. Their responses are read by the teaching team and inform the next iteration — not filed away.

Certificate Integrity

Certificates are issued only to students who complete the required work and submit the assessed project. Attendance alone does not qualify.

Expertise and Approach

AI Education That Respects the Learner

The field of AI development has expanded rapidly, and so has the volume of learning material available to anyone with an internet connection. What has not kept pace is the quality of structured guidance available to people who are starting from scratch or moving into the field from adjacent roles — developers, analysts, and professionals who are technically capable but have not yet worked with machine learning tools in depth.

Cerdik Code focuses on this gap. Our programmes are not designed for people who have already completed a machine learning degree; they are designed for people who are working toward their first serious understanding of what these systems actually do. We begin with the fundamentals — what a model is, what training involves, what the outputs mean — and we build from there with enough pace that students feel engaged, but not so fast that they lose the thread.

Each of our three tracks — AI Literacy for Beginners, Machine Learning Practitioner, and Advanced Deep Learning Studio — was developed by practitioners who teach from their own working experience. The curriculum reflects the tools and approaches that are actually in use in Malaysian and regional industry settings, not a syllabus assembled from textbooks alone.

Our location in George Town, Penang places us at the centre of one of Malaysia's most active technology communities. We draw on networks built through years of industry work to keep our teaching current and to create pathways for students who want to continue developing after their programme ends — through the alumni circle and through introductions to professional communities that our mentors are part of.

If you are at a point where you want to take AI seriously but are not sure where to begin, or if you have been coding for a while and want to build out your understanding of machine learning or neural networks, Cerdik Code is worth a conversation. We are happy to talk through which path fits your background and goals before you commit to anything.

Next Step

Have a Question for Us?

We respond to every enquiry within one business day. If you are not sure which track suits your background, just tell us where you are starting from and we will point you in the right direction.

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