About Khun Academy
Learning AI at the pace it deserves
We started Khun Academy because we noticed that most online courses on machine learning and AI prioritise pace over comprehension. We thought the opposite was worth trying.
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How Khun Academy began
Khun Academy opened its courses in early 2023, operating out of Suthep in Chiang Mai. The founders — two researchers who had spent years teaching and doing applied machine learning work — had grown frustrated with the gap between introductory AI content and the level of understanding needed to do real work in the field.
The school started with a single course: Statistical Foundations for AI. The reasoning was simple. Statistics underlies nearly everything in machine learning, and a shaky statistical foundation tends to become a ceiling. Students who understood the material carefully did better work later. Those who had absorbed surface-level explanations from fast-paced courses often struggled when theory and practice diverged.
The Computer Vision Track followed about a year later, designed as the same kind of careful, sequential study applied to a specific domain. The Reinforcement Learning Programme came after that — a longer engagement, suited to learners ready to spend real time with a difficult subject.
Today Khun Academy remains a small school. We have kept it that way on purpose. Smaller cohorts mean more substantive mentor engagement. We are not trying to be the largest AI school in Southeast Asia — we are trying to be the one where the learning actually sticks.
Mission
What we are here to do
Our goal is to help learners develop a working understanding of AI concepts — one that holds up under real conditions, not just assessment conditions. We measure success not by completion rates but by whether students can apply what they have studied to new problems with appropriate confidence.
The People
Who teaches here
Parinya Charoenwong
Lead Instructor · Statistics & ML
Parinya holds a doctorate in applied statistics from Chulalongkorn University and spent six years working on forecasting systems before turning to teaching. He leads the Statistical Foundations course and mentors students across all three tracks.
Nattaya Wongchai
Computer Vision Instructor
Nattaya worked for four years in computer vision research at a Bangkok-based engineering firm before joining Khun Academy. She designed the Computer Vision Track curriculum and leads all mentor review in that programme.
Somchai Kittipong
Reinforcement Learning Instructor
Somchai has a background in robotics and control theory and spent several years working on RL-based systems before moving into education full time. He leads the Reinforcement Learning Programme and is known for patient, careful written feedback.
How We Work
Our academic standards
Transparent prerequisites
Every course states clearly what prior knowledge it assumes and what it does not. We send a short background assessment before enrolment to confirm fit.
Written mentor feedback
Assignments and projects receive substantive written responses from an instructor — not automated scoring or brief comments. Feedback typically arrives within three business days.
Student data protection
We collect only the information needed to run your enrolment. Student work and correspondence are never shared with third parties. See our Privacy Policy.
Curriculum review cycle
Each course is reviewed and updated annually. When the research landscape shifts — as it does in RL especially — we revise the material to reflect current practice, not just historical context.
Small cohort sizes
We limit enrolment in each intake to keep mentor workload at a level where feedback is thorough. This means our intakes fill on a schedule — contact us about upcoming dates.
Honest communication
If a course is not a good match for your background at the moment, we will say so plainly and suggest a more suitable path. We are not interested in enrolments that are unlikely to go well.
Our Approach to AI Education
Depth, sequence, and honest scope
The field of machine learning and artificial intelligence is broad enough that no course can cover it fully. What distinguishes a useful course from a superficial one is whether it takes a defined part of the field seriously — following ideas down to where they become difficult, rather than papering over that difficulty with high-level summaries.
At Khun Academy, each of our three courses picks a domain and works through it with care. Statistical Foundations covers the mathematics of reasoning under uncertainty with enough rigour that students can read primary sources after completing it. The Computer Vision Track builds from image data handling through to modern convolutional architectures, with the aim that students leave able to scope and execute a real computer vision project. The Reinforcement Learning Programme takes twenty weeks because the subject genuinely requires that time — the concepts are interrelated in ways that make rushing through them counterproductive.
We are based in Chiang Mai, which gives us access to a community of researchers and practitioners working across Southeast Asia. Our instructors maintain active connection to applied work, which keeps the curriculum grounded in problems that actually arise in practice rather than in problems that are merely convenient to teach.
Our students come from a range of backgrounds — engineers transitioning into ML roles, researchers adding AI methods to existing technical skill sets, and academics exploring adjacent fields. What they share is a preference for understanding over surface familiarity, and a willingness to put in the time that serious study requires.
Take the next step
Find out if our courses suit your background
Send us a message and we will help you assess whether the course level fits what you already know. No obligation — just a conversation.
Get in Touch