What Learners Say
Honest accounts from people who've been through the courses
These are genuine experiences — varied, specific, and including the things that were difficult alongside the things that worked.
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Learner Reviews
From the cohorts
Wanida Phromthong
Marketing analyst · Bangkok
I came in knowing absolutely nothing about Python — not even what a variable was. The first two weeks felt slow, which in hindsight was exactly right. By week five I was writing my own data cleaning scripts and actually understanding what they did. The mentor feedback was what made the difference; I'd get a paragraph of notes on each submission explaining what worked and what to rethink.
Intro to AI & Python · May 2025
Kritsada Suwan
Software developer · Chiang Mai
I had some Python background from work but deep learning was new. The workshop moved faster than the intro course, which suited me. The capstone project took longer than I expected — I probably underestimated how much iteration goes into actually training a model on a messy dataset. That said, finishing it felt genuinely satisfying in a way that completing a quiz never does.
Deep Learning Workshop · April 2025
Nattaya Jaiyen
Data coordinator · Chiang Rai
Working full-time and studying at the same time is genuinely hard. Codeloom knows this — the pacing doesn't assume you can give eight hours on a weekday. I had a rough patch around month three of the engineering program and reached out to ask about catching up. The response was practical rather than reassuring: they helped me rearrange which modules to prioritise. That kind of support matters.
Applied AI Engineering · May 2025
Pawin Thongchay
Freelance designer · Bangkok
Honestly, I wasn't sure after the first week whether I'd chosen the right place. The pace was slower than I wanted. But I stayed and I'm glad I did — by week four it clicked why things had been introduced in that order. I'd taken a faster course before that left me able to copy code without understanding it. This was different. I can now write things from scratch and debug them without copying from Stack Overflow.
Intro to AI & Python · April 2025
Supaporn Rakthai
Research assistant · Chiang Mai
The weekly sessions with Kasem were the highlight of the Deep Learning Workshop for me. He has a way of explaining gradient descent that makes it feel almost obvious in retrospect. I asked some genuinely confused questions and never felt embarrassed for doing so. The code review feedback was occasionally blunt — in a good way. You know exactly what to fix and why.
Deep Learning Workshop · May 2025
Thanakrit Lertphon
Junior analyst · Lampang
I enrolled in the engineering program with about eighteen months of Python experience. The first two months covered things I knew — but the framing was different. I kept learning how to think about engineering problems, not just write code for them. Months four and five on deployment were genuinely new and difficult. I needed more time there than the schedule assumed, and my mentor adjusted accordingly.
Applied AI Engineering · March 2025
Learner Journeys
From starting point to outcome
Three detailed accounts of what the experience looked like from beginning to end.
Wanida · Marketing → Data-aware analyst
Intro to AI & Python · 8 weeks
Starting point
Working in marketing analytics using Excel and Google Sheets. Wanted to work with larger datasets and understand what the data team's Python scripts were doing — couldn't follow even basic code.
What the course covered
Python fundamentals, pandas for data manipulation, exploratory analysis, and a guided project using a real customer dataset from a retail business. Weekly mentor sessions helped clarify where things weren't landing.
After completing
Can now read and modify the team's Python scripts. Has written three independent analysis scripts for her own work. Plans to enrol in the Deep Learning Workshop in the next cohort.
"I didn't expect the certificate to feel like much, but it mattered to me because I knew what was behind it."
Thanakrit · Analyst → ML-capable engineer
Applied AI Engineering Program · 6 months
Starting point
Junior analyst with Python experience but no knowledge of model deployment or engineering workflows. Could train models in Jupyter notebooks but couldn't put anything into production.
What the programme covered
End-to-end pipeline development, experiment tracking, deployment via FastAPI, monitoring, and collaborative Git workflows. Portfolio built across four projects, each adding a layer of complexity.
After completing
Moved into a junior ML engineering role at a Chiang Mai-based startup. Portfolio from the programme was cited in interviews as concrete evidence of practical capability.
"Month five was hard. But Nathapong never made me feel like the difficulty was my failure — it's just that deployment is genuinely complex."
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+66 53 216 8497Address
Nimmanhaemin Soi 9, Chiang Mai
Office Hours
Mon–Fri 9:00–18:00 ICT
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