About Cortexa
A school built around
how people actually learn
Cortexa was put together by people who believed that learning AI development should be accessible, structured, and free of hype — designed so the material holds up after the course is over.
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Started in Bangkok, aimed at learners everywhere
Cortexa came out of a straightforward observation: most materials for learning machine learning and AI development were either too shallow to be useful or assumed an academic background that most working professionals didn't have.
The founders — a small group of developers, educators, and data practitioners based in Bangkok — spent about a year designing course structures that moved at a deliberate pace, explained the reasoning behind technical choices, and built in regular checkpoints rather than leaving learners to sink or swim.
The first cohort ran in early 2023 with around forty people. Most were working adults from Thailand, Malaysia, and Indonesia who wanted to understand what machine learning actually involved — not just the marketing around it. The feedback shaped how the three current tracks are designed.
Since then, Cortexa has worked with over four hundred learners. The core team has stayed small on purpose: smaller means the course content stays current, the mentorship stays personal, and the feedback that gets written is actually read.
Mission & Values
What we hold ourselves to
Honesty about what AI can and can't do
Course content describes AI systems accurately. We don't frame things as magic, and we don't promise outcomes we can't substantiate.
Pacing that fits working adults
Every track is structured around the reality that learners have jobs, families, and limited concentrated time. Content is chunked accordingly.
Practice before polish
Building something that works — even if rough — teaches more than reading about a clean example. Exercises come before explanations, not the other way around.
Feedback that's specific and direct
Milestone reviews and mentorship sessions are written or discussed plainly — what worked, what didn't, and what to look at next.
The Team
People behind the courses
Nawin Khamchai
Co-founder · Curriculum Lead
Designed the Foundations track and oversees how course content is sequenced across all three programmes. Previously worked in data engineering in Singapore.
Piyanan Rattanaporn
Co-founder · Mentorship Programme
Manages the Applied and Capstone tracks, including mentor selection and feedback quality. Has a background in applied ML research and course facilitation.
Somchai Thanakit
Technical Instructor
Writes exercises and reviews submitted model code for the Applied track. Has spent the past six years building production ML pipelines for mid-sized companies in Southeast Asia.
Standards
How we maintain course quality
These aren't policies written for a brochure — they're the actual practices that determine whether what we ship is worth a learner's time.
Regular Content Review
Course materials are reviewed at minimum every six months. Modules that reference specific libraries or frameworks are updated when those tools change in ways that affect learner exercises.
Mentor Vetting
Mentors on the Capstone track are practitioners with verifiable work in AI or ML-adjacent roles. We review a sample of their written feedback before they join the programme.
Exercise Review Process
All course exercises are tested by people outside the team before they reach learners. Exercises that produce unclear or misleading results are revised before release.
Data Privacy
Learner data — submitted work, contact information, progress records — is held securely and is not shared with third parties. See our Privacy Policy for detail.
Cohort Feedback Loop
We collect structured feedback at the end of each cohort. Specific suggestions about pacing, clarity, or exercise difficulty are reviewed by the curriculum team within two weeks.
Accessible Language
Technical terms are introduced with clear definitions. Where jargon is unavoidable, it's explained in plain language before it's used in exercises or assessments.
Approach
What makes Cortexa different from self-study
Most online resources for AI development are either scattered tutorials, academic lectures repurposed for the web, or courses that move so fast the learner is left copying code without understanding why it works. Cortexa was designed to sit in a different space: structured enough to have clear progression, slow enough that concepts have time to settle, and practical enough that learners end each module with something they've built.
The three tracks at Cortexa follow a logical sequence. A learner starting with Foundations is working through programming for data, probability, and the basic mechanics of how a model learns — not abstract theory, but the actual operations behind gradient descent, feature engineering, and evaluation metrics. By the time they reach the Applied track, they are writing real training loops and making informed choices about their approach rather than following a recipe.
The Capstone track is designed for learners who want to go further. Working with a practitioner mentor over several weeks, they take on a substantial project from problem framing through to a presented result. This isn't a walk-through — the mentor gives direction and feedback, but the learner owns the decisions.
Cortexa is based in Bangkok and has primarily served learners across Southeast Asia, though the courses are conducted in English and open to anyone. The team is small, which means responsiveness is high and course updates happen quickly when the field changes. Learners deal with the same people throughout their programme — there's no large support team routing enquiries between departments.
The field of AI development moves quickly, and no course can cover everything. What Cortexa tries to do is give learners a foundation that holds up — an understanding of how models work, how to evaluate them, and how to keep learning independently after the programme ends.
Get in touch
Questions about our programmes or approach?
Our team is happy to walk through which track fits your background and what to expect before you commit to anything.
Contact Us