What People Say After Studying With Us
Accounts from people who have completed one or more of our courses, in their own words.
Back to Home4+
Years running AI courses
340+
Learners enrolled
4.7/5
Average learner rating
87%
Course completion rate
From the People Who've Been Through the Courses
Anutida Thongchai
Bangkok — First Steps in AI
I had tried to learn Python twice before and both times got stuck after about two weeks. The difference here was that each week built on the previous one in a way that actually made sense. I didn't feel like I was being thrown into the deep end. Finished the course in twelve weeks — slightly over, because of a busy month at work — and I felt fine about that.
May 2025
Phitchapa Wongkham
Chiang Mai — Building & Testing Models
The model evaluation section was particularly useful. I'd read about train/test splits before but this was the first time I really understood why getting it wrong matters. The feedback on my projects was detailed and specific — not just "good job". One note: I would have liked a bit more material on neural networks, but I understand the course is scoped intentionally narrower than that.
April 2025
Krit Panyacharoen
Bangkok — Guided Project Track
Finishing the project track was genuinely satisfying. I came in with an idea for a demand-forecasting model and finished with a working prototype I could actually explain. My mentor was helpful in keeping the scope realistic — I had a tendency to expand it in ways that would have made it unfinishable. The final presentation review was thorough and honest.
May 2025
Sirikanya Nantasin
Pattaya — First Steps in AI
Worth it as a first step into technical work. The instructor who reviewed my exercises wrote comments that made me think, not just corrections. I'm now halfway through the second course.
May 2025
Tawan Limphirat
Bangkok — Building & Testing Models
I came from a finance background with some exposure to Excel modelling. This course showed me the gap between that and actual machine learning in a clear, non-condescending way. The guided projects were more challenging than I expected — which was a good thing. Takes commitment but it's manageable alongside a working week.
April 2025
Natnicha Maneerat
Bangkok — Guided Project Track
The mentoring was the part I wasn't sure about before I enrolled — I wasn't sure how much guidance I'd actually get. Turned out to be very hands-on. We had regular check-ins and my mentor pushed back on my assumptions in ways that strengthened the project. I now have something I'm comfortable showing in job applications.
May 2025
Three Learner Journeys in Detail
What the course experience looked like from start to finish, in specific situations.
Burak Kaplan — Finance Analyst, Bangkok
Completed: First Steps in AI + Building & Testing Models
The Starting Point
Burak had strong Excel skills but no programming background. He wanted to work with Python for data work but found online resources too scattered and hard to self-pace alongside a demanding job.
What He Did
Started with First Steps in AI over about thirteen weeks (slightly extended due to workload peaks). Moved to Building & Testing Models three months later. Used the structured weekly format to carve out four hours on weekend mornings.
Where He Got To
By the end of the second course he was writing Python scripts for his own data tasks at work and had built two supervised models. He describes the second course as "the one that made things real."
"I wasn't going to become an ML engineer — that wasn't the goal. The goal was to stop being helpless around data tools. Both courses helped with that in a way that actually stuck."
Wipharat Phommasack — Software Developer, Bangkok
Completed: Building & Testing Models + Guided Project Track
The Starting Point
Wipharat was a working web developer who knew Python basics but had never applied it to ML. He wanted a structured path rather than piecing together tutorials.
What He Did
Joined directly at the intermediate course level after a brief assessment. Completed Building & Testing Models, then enrolled in the Project Track and built a classification model for a real dataset from his domain.
Where He Got To
Produced a documented project with an 82% validation accuracy, which he presented clearly in a subsequent technical interview. He credited the mentor's feedback on project scope for keeping it practical and completable.
"The project track mentoring was the part I underestimated before I started. It changed how I think about scoping technical work, not just ML projects."
Have a Question Before Enrolling?
Phone
+66 2 218 6473Address
87 Phaya Thai Road, Ratchathewi
Bangkok 10400, Thailand
Office Hours
Mon – Fri: 9:00 – 18:00
Sat: 10:00 – 15:00
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