Why Panya Code
What you get that most programmes do not offer
Part-time AI education built around how practitioners actually work — not around what looks impressive in a prospectus.
Back to HomeCore advantages
Six things that shape every cohort
Instruction from active practitioners
Everyone who teaches at Panya Code works in the field. The examples, the edge cases, and the debugging approaches in each session come from current professional practice, not from recreating textbook scenarios.
Designed for employment alongside
Sessions are scheduled in the evening or on weekend mornings. Each week's scope is defined and bounded, so learners can plan around it without rearranging their professional commitments.
Projects that accumulate
Each weekly project builds on the previous one. By the final week, learners have a coherent body of work covering the full arc of the programme — not a collection of isolated exercises.
Small cohorts, specific feedback
Cohort sizes are kept small so the teaching team can give feedback on each learner's specific work — not just general guidance that applies equally to everyone regardless of approach.
Recorded walk-throughs for every session
Every live session has a corresponding recorded walk-through available for the duration of the cohort. Learners who miss a session or want to revisit a section can do so without waiting for the next intake.
Pricing that reflects the market
Fees are set with Bangkok learners in mind. The cost of a full programme is comparable to a few months of a typical streaming learning subscription, but with live instruction, feedback, and office hours included.
In more depth
Expertise grounded in professional practice
Both lead instructors currently work in applied AI roles. Krit brings eight years of data science experience in financial services; Siriwan works in AI infrastructure for a logistics operation. Their professional work informs every session — when a learner asks why something is done a particular way, the answer typically comes from a real situation rather than a theoretical framework.
This matters because AI development involves decisions that textbooks rarely address honestly: when to stop tuning a model, how to communicate uncertainty to a non-technical stakeholder, what a realistic deployment pipeline looks like for a small team. These are the things practitioners know, and they find their way into the curriculum.
Tools that are in current use
The curriculum covers Python with the scientific-computing stack, pandas and polars for data work, scikit-learn and gradient-boosted tree implementations for the machine learning track, and MLflow, Docker, and cloud deployment patterns in the engineering programme. These are the tools learners will encounter in professional contexts, not proprietary environments that do not transfer.
The curriculum is reviewed after each cohort and updated before the next one. When a tool's role changes in professional practice, the session material reflects that.
Support that responds to the actual question
Office hours are open rather than structured. A learner can bring any question from the programme — a project they are stuck on, a concept they want to test their understanding of, a question about how something would work differently in their own context. The teaching team responds to the specific question, not to a version of it that fits a pre-prepared answer.
Written support during the week is also available for shorter questions. Most messages receive a response within one working day.
Fees set with Bangkok learners in mind
The Python and Data Fundamentals cohort is ฿4,800. The Machine Learning Track is ฿9,500. The End-to-End Engineering Programme is ฿14,500. These fees cover all session access, recordings, project briefs, feedback, and office hours for the full programme — there are no additional charges for materials or access.
For the longer programmes, a two-part payment arrangement can be discussed at the time of enrolment.
Progress that is visible over time
Because projects build on each other, learners can see their own progress in concrete terms — not just through a course completion percentage, but through the growing complexity and coherence of their own work. By the end of the Engineering Programme, a learner has a portfolio project they chose themselves, built through the programme, and can speak to directly in a professional context.
How we compare
Panya Code vs typical AI courses
| Feature | Typical online course | Panya Code |
|---|---|---|
| Instructor availability | Pre-recorded only, no direct access | Live sessions + office hours |
| Feedback on your work | Automated quiz scoring only | Project feedback each week |
| Cohort size | Thousands of simultaneous learners | Small groups, individual attention |
| Instructor background | Variable — often academic or content-focused | Active practitioners in the field |
| Project structure | Isolated exercises, no continuity | Cumulative projects that build a portfolio |
| Schedule flexibility | Self-paced (easy to delay indefinitely) | Structured pace with recordings for review |
| Tools covered | Often proprietary or tutorial-only | Industry-standard tools in current use |
What sets us apart
Things we do that are uncommon in online learning
Curriculum updated between cohorts
After every cohort, we review what worked and what did not. Project briefs, session sequencing, and tool choices are updated before the next intake. Learners always get current material rather than a version from two years ago.
Office hours without a pre-set agenda
Office hours at Panya Code are genuinely open. A learner can bring anything they are working through — a stuck project, a concept they want tested, a question about how their work would be received in a professional context. There is no queue of scripted questions.
Built for Thailand, accessible from anywhere
Sessions are scheduled around Bangkok working hours and the practical realities of commuting in the city. The programme is online, so learners based elsewhere in Thailand — or in compatible time zones regionally — can join without travelling.
Portfolio you can speak to directly
Because projects are cumulative and learner-chosen in the Engineering Programme, the portfolio a learner leaves with is genuinely theirs. They know every decision in it, which means they can discuss it clearly in a professional context without relying on a script.
Milestones
Panya Code in numbers
7+
cohorts completed since 2023
120+
learners across all programmes
3
structured programmes at distinct levels
4.7
average learner satisfaction (out of 5)
Recognised by ThaiAI Forum
Listed among emerging applied AI education providers in Thailand in the 2024 community survey.
Curriculum aligned with industry tools
All tools in the curriculum are verified against current job listings and practitioner surveys before each cohort intake.
Maintained cohort completion rate
Over 85% of enrolled learners complete their chosen programme through to the final session and project.
Ready when you are
Enquire about the next available intake
If you would like to know which programme is the right fit for your background and goals, send us a message. We will follow up with available dates and any questions we have about your experience.