Teaching AI the Way It Should Be Learned
We started Cortexia because the gap between "learning about AI" and "being able to build with AI" was too wide. We're working to close it — one programme at a time, with real projects and real mentors.
Back to HomeWhere Cortexia Came From
Cortexia was set up in Subang Jaya with a straightforward aim: to offer AI and machine learning education that's built around doing things, not just reading about them. The founders — practising engineers and educators — had watched too many learners finish online courses without being able to write working code or explain what their models were actually doing.
We built our three programmes from scratch, starting with the question: what does a learner actually need to be able to do at the end of this, and what's the clearest path to get there? The result is a curriculum centred on guided practice, structured feedback, and portfolio work that belongs to the learner.
We're based in Selangor and run all our sessions online, which means learners from across Malaysia — and the wider region — can join without relocating. Sessions are timed for Malaysian working hours, and all recordings are kept available throughout the programme.
What We Stand For
Honest about outcomes
We don't make promises about employment or income. We focus on whether learners can actually build things by the end of the programme.
Practice over theory
Concept explanations are kept tight. Most of the time is spent writing and reviewing code, working with data, and building projects.
Respectful of learner privacy
We collect only what we need to run the programme. We don't share learner details with third parties for commercial purposes.
Transparent pricing
Programme fees are listed clearly and cover everything — materials, mentoring, and portfolio support. No hidden costs.
Who Runs the Programmes
Mentors at Cortexia are working engineers and educators, not instructors who stopped coding when they started teaching.
Razif Hamdan
Razif spent eight years writing data pipelines and classification models for logistics firms in the Klang Valley before joining Cortexia. He leads the Foundations cohort and has a talent for making Python feel approachable without dumbing things down.
Su Lin Teoh
Su Lin's background is in applied machine learning for fintech, where she spent years building and evaluating models in regulated environments. She leads the ML Engineering track, with a particular focus on clean, testable model code and sensible evaluation practices.
Arjun Krishnamurthy
Arjun has worked on deep learning systems for computer vision and NLP across projects in Malaysia and Singapore. He leads the Advanced programme, guiding learners through the capstone with close one-to-one support and emphasis on deployment-ready engineering habits.
Our Approach to Quality
These are the standards we hold ourselves to across every programme and every cohort.
Curriculum Review
Programme content is reviewed between cohorts. Tooling, datasets, and project briefs are updated to reflect how things are actually done in current practice.
Mentor Accountability
Mentors respond to learner questions within one business day. Code review feedback is specific — not generic — and tied to what was actually submitted.
Data Privacy
Learner data is handled in line with Malaysian personal data protection requirements. We don't share enrolment information with third parties for advertising purposes.
Cohort-Sized Groups
We keep cohorts small enough that each learner gets proper mentor attention. If a cohort fills, we open a waiting list for the next intake rather than overloading the current group.
Portfolio Integrity
Portfolio projects are built by the learner with mentor guidance — not copied from templates. Mentors check that the work reflects the learner's own understanding.
Learner Support
Learners can contact the team by email or via the cohort channel throughout the programme. We don't disappear between live sessions.
AI Education in Malaysia: What We're Building Towards
The demand for people who can work meaningfully with machine learning and AI systems has grown steadily across Malaysia's tech, finance, and logistics sectors. At Cortexia, we're not trying to turn every learner into a research scientist — we're focused on the more grounded goal of helping working adults in Selangor and beyond build the kind of practical AI skills that are actually useful in the workplace or in personal projects.
Our three programmes — AI Foundations, Machine Learning Engineering, and Advanced AI Development — are structured to meet learners where they are. Someone with no coding background can start with the Foundations track, spend eight weeks building real Python skills and working with data, and end with a portfolio project they understand and can explain. From there, the ML Engineering track picks up with structured model-building work, and the Advanced programme takes learners through deployment and serious project development.
We're selective about what we teach. Every topic in our curriculum is there because it's part of how AI work actually gets done — not because it sounds impressive. That means less time on theoretical depth that doesn't translate to practice, and more time on writing clean code, debugging real errors, understanding data, and building things that run.
Cortexia is a small school. We think that's a strength. Our learners aren't numbers in a cohort of hundreds — they're people with names and specific questions and code that a mentor has actually read. We're working to keep it that way as we grow.
Ready to start building?
Send us an enquiry and we'll help you work out which programme fits your background. No pressure — just a clear conversation about what makes sense for you.
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