What Students Have to Say
Honest accounts from people who came to Wichaset with different backgrounds and left with new skills they could put to use.
← Back to Home340+
Courses completed
4.8
Average rating (out of 5)
92%
Completion rate
3+
Years teaching AI in Bangkok
Student Reviews
A range of perspectives from students who enrolled in our three tracks.
Pattaraporn Phumsiri
Data Analyst · Bangkok
"I took the Foundations course because I wanted to understand what my engineering colleagues were talking about. The instructor did not assume any prior maths knowledge, which made the first few sessions much less stressful than I expected. By the end I had built a working regression model on our team's actual data — something I would not have thought was possible a month before."
June 2025 · ML Foundations
Wichit Charoenkul
Software Developer · Nonthaburi
"I already knew some Python so the early Computer Vision sessions felt straightforward — but the CNN sections were genuinely new to me. The instructor slowed down when we got there, which I appreciated. A couple of the between-session assignments were quite demanding, but the feedback I received was thorough and helped me get unstuck. Left with a working image classifier and a certificate to show for it."
June 2025 · Computer Vision
Natthanee Wongwai
Postgrad student · Chulalongkorn
"Applied Deep Learning was the right level for me. I had done some self-study before attending but always felt shaky on the theoretical side. Sirawit explains backpropagation and gradient descent clearly without skipping the maths, but also without making it feel overwhelming. The small group size meant I could ask about things I had been quietly confused about for a while."
July 2025 · Applied Deep Learning
Thanakorn Klahan
Operations Manager · Bangkok
"Coming in with no coding background at all was nerve-wracking, but the Foundations course is genuinely built for that. The instructor checks in constantly and the group is small enough that you do not feel embarrassed asking basic questions. After six weeks I can read a Python script without panicking, which is more than I expected."
June 2025 · ML Foundations
Siriporn Rodprasert
Product Designer · Bangkok
"The Computer Vision track was a solid experience. Nattaya is a patient teacher and the walkthroughs during sessions were easy to follow. I found the final project took longer than I expected to complete — partly because I wanted to go deeper into it — but the written feedback I received was detailed and genuinely useful. I would recommend it to anyone curious about how image AI works."
July 2025 · Computer Vision
Aphisit Buraphakorn
IT Consultant · Bangkok
"I came to Applied Deep Learning after doing the ML Foundations course six months earlier, and the progression felt natural. Sirawit builds neural networks from first principles rather than just handing you a pre-built framework and saying 'run it' — that approach meant I actually understood what was happening inside the model. The PyTorch section in particular was very well paced."
July 2025 · Applied Deep Learning
How Students Applied Their Learning
Three short accounts of how Wichaset courses led to concrete outcomes.
The Situation
A logistics coordinator in Bangkok wanted to use machine learning to flag delivery delays before they occurred. She had no coding experience and was unsure where to begin.
What Changed
She enrolled in the ML Foundations track and spent six weeks learning Python and supervised classification. By the final session she had trained a basic delay-prediction model on a sample of her company's shipment data.
The Outcome
The prototype was refined with colleagues and presented internally. Within three months of the course finishing, a version of the model was in use for a subset of routes, flagging roughly 70% of delays 24 hours in advance.
"The course gave me enough to build something real. I am still learning, but I am learning by doing now rather than just reading." — ML Foundations graduate, June 2025
The Situation
A product designer at a consumer goods company wanted to automate quality inspection on a packaging line by detecting surface defects from camera images.
What Changed
He completed the Computer Vision Track and learned how to use OpenCV for preprocessing and PyTorch for building a CNN-based classifier. The final project used sample images from the company's production line.
The Outcome
The proof-of-concept model reached 87% accuracy on a held-out test set. The project was enough to secure internal funding for a proper pilot with a larger dataset and engineering support.
"I came in knowing what I wanted to build. The course taught me how to actually build it." — Computer Vision graduate, July 2025
Reach Out Directly
Phone
+66 2 307 5284Address
240 Thanon Rama IX,
Huai Khwang, Bangkok 10310
Working Hours
Mon – Fri: 10:00 – 20:00
Sat: 09:00 – 17:00
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