What people say after taking the courses
Learners at different stages and from different backgrounds — sharing what the experience was actually like.
340+
Learners enrolled
4.7
Average satisfaction score
91%
Course completion rate
3
Focused AI tracks
From the learners
Reviews submitted after completing a course. We have shared them here without editing the wording.
Wipawee Phanit
Data analyst, Bangkok
"I have tried two other online ML courses and both moved too fast for me to keep up. The Foundations track at Samong was different — each lesson built on the previous one and I actually felt like I understood what I was doing before moving to the next section. The exercises helped a lot."
June 2025 · ML Foundations
Thanakorn Jirawat
Software developer, Chiang Mai
"The MLOps track covered things I had been piecing together from documentation for months. Having it structured in one place made a real difference. The section on monitoring was particularly good — it addressed failure cases that I had encountered at work but not understood properly."
June 2025 · Model Deployment & MLOps
Siriporn Rojana
Linguist, Bangkok
"I came to the NLP Projects track from a language background, not a technical one. The instructor was patient when I asked basic questions and the Thai-language examples were directly relevant to the kind of work I am interested in. I finished the three projects and felt like I had built something real."
July 2025 · NLP Projects
Apisit Kongkham
Engineering student, Bangkok
"I took the ML Foundations course between semesters. It complemented what I was studying at university but explained things in a more practical way. The exercises were harder than I expected, which was a good thing. I had to think, not just copy. Worth the time."
June 2025 · ML Foundations
Nantawan Suksawat
Product manager, Bangkok
"I am not a developer and I was unsure whether the MLOps course would be too technical for me. It was challenging in places, but the material was written clearly enough that I could follow it. I sent a question about Docker and got a thorough response the next morning. That kind of support made a difference."
July 2025 · Model Deployment & MLOps
Pimchanok Tharawat
Researcher, Chulalongkorn University
"The NLP Projects track was exactly what I needed for my research. The pace was right and the instructor feedback on each project was specific and useful — not just 'good work'. I appreciated that the course did not try to cover everything; it covered what it covered well."
July 2025 · NLP Projects
Learner journeys
Three longer accounts of where learners started, what they did, and what changed.
Challenge
Moving from spreadsheets to ML
Kanchana was a marketing analyst who had been working in Excel for four years. She wanted to understand how machine learning worked but did not know Python and had no clear starting point.
How she approached it
She enrolled in ML Foundations and studied in the evenings after work, roughly four hours a week. She used the exercises to practice each concept before moving on, and asked questions when something was unclear.
After the course
Over six weeks, she completed the track and submitted a final project predicting customer churn. She was able to run her own analysis at work using what she had learned.
"I did not expect to be able to do this in six weeks. I still have a lot to learn but I can actually write and run code now."
Challenge
Getting a notebook model into production
Pakorn was a junior data scientist at a logistics company. He had trained models in Jupyter but had no idea how to deploy them so the operations team could use them. His team did not have the expertise to help.
How he approached it
He took the MLOps track over eight weeks, fitting it around a demanding project at work. He focused especially on the Docker and CI/CD sections, which were the parts most relevant to his situation.
After the course
He deployed his first model to a staging environment within a month of finishing the course. It was the first time his team had a machine learning system running outside a notebook.
"The monitoring section was where it clicked for me. I finally understood why models that worked in training were behaving strangely once deployed."
Challenge
Applying NLP to Thai legal text
Malee was a paralegal interested in automating document classification for her firm. She had some Python experience but no knowledge of NLP tools, and she specifically needed to work with Thai-language documents.
How she approached it
She chose the NLP Projects track because of its Thai-language content. She worked through all three projects, adapting two of them to use legal document excerpts from her own work.
After the course
She built a basic classification pipeline for incoming correspondence. It did not replace manual review but reduced the time spent on initial sorting by around 40%.
"Having Thai examples in the course was the part I was most nervous about finding elsewhere. It was one of the main reasons I enrolled."
Have a question before enrolling?
Phone
+66 2 861 4093Address
18 Thanon Convent, Silom, Bang Rak, Bangkok 10500
Working Hours
Mon–Fri: 09:00–18:00 ICT
Sat: 10:00–14:00 ICT
Ready to find out if Samong is the right fit?
Send a message and we will get back to you with the information you need to decide.
Get in Touch