What you actually get from learning here
Most AI courses teach you to follow a walkthrough. We teach you to scope, build, and document something of your own. That gap matters.
Back to HomeSix things that matter here
A quick read before going into detail.
You complete a real project
Not a tutorial clone — a project you scoped, built, and documented yourself.
Mentors who have shipped software
All mentors have verifiable experience in production AI and ML systems.
Cohorts capped at 16
Mentorship only works at small scale. We enforce the cap every cycle.
Editorial reading list, not video dumps
The library is curated for depth. You read to understand, not to fill a progress bar.
Paced for full-time workers
Sessions are scheduled around working hours. Three to five hours per week is enough.
A documented output you can share
A written technical report that shows your thinking, not just your ability to copy code.
What each benefit means in practice
Practitioner expertise
Neuralforge mentors have built classification systems, NLP pipelines, and recommendation engines at Bangkok-based companies. They are not researchers explaining theory — they are practitioners explaining the decisions they actually make.
- Production ML experience, not academic only
- Cross-sector background: fintech, logistics, analytics
- Mentors reviewed and requalified every year
Curriculum grounded in current tools
The project course uses the same Python-based ML tooling you would encounter on the job — scikit-learn, pandas, lightweight deployment with FastAPI or Streamlit, and version control. We do not teach you to use tools that were standard five years ago.
- Current Python ML stack throughout
- Dataset sourcing and preparation included
- Light deployment covered in the project course
Responsive support throughout
Each participant has access to their mentor and the program team between sessions. Questions about a dataset, a model choice, or a documentation structure get answered — not redirected to a FAQ page or a community forum.
- Direct mentor contact between sessions
- Draft feedback before final submission
- Library members have access to editorial team
Transparent, tiered pricing
Programs are priced to reflect what they involve — the project course (฿4,200) costs less than the cohort program (฿31,000) because it involves less direct mentorship time. The reading library (฿8,500/yr) is priced as an ongoing resource, not a course. There are no hidden fees and no upsell tracks.
- Three distinct price points for different engagement levels
- No upsell tracks or hidden modules
- Full fee details before enrolment
Outcomes you can point to
Participants finish with a written technical report describing a project they built — scope, data, methodology, findings, and known limitations. That document is useful when talking to employers, clients, or colleagues. A certificate PDF is not.
- Written project report as primary deliverable
- Documentation template provided and reviewed
- Projects address real data, not toy datasets
How we compare to typical options
A direct comparison without naming anyone — the patterns are common enough.
| Feature | Typical online platforms | Neuralforge |
|---|---|---|
| Project completion | Tutorial walkthroughs only | Own project from start to finish |
| Cohort size | Hundreds or thousands | Maximum 16 per cohort |
| Direct mentor access | Forum or Q&A only | Direct contact between sessions |
| Deliverable | Completion certificate | Written technical report |
| Mentor background | Varies, often academic | Industry practitioners only |
| Pace | Self-paced (often abandoned) | Structured but fits full-time work |
| Reading resources | Auto-generated or scraped | Editorially curated long-form texts |
Things we do that most programs do not
Documentation template and draft review
We give every participant a structured template for their final report and review at least one draft before they submit. Most programs end when the video ends.
Hard cohort cap, enforced every cycle
We turn away enrolments when the cohort is full. That cap is not a marketing claim — it is the reason mentorship rounds work.
Library with editorial curation and moderated discussion
The reading library is not a link dump. The editorial team selects and annotates texts, and one moderated discussion per month helps participants process what they read.
Scope honesty before enrolment
We tell applicants directly if a program is not a good fit for their background. That saves everyone time and keeps the cohort working at a consistent level.
By the numbers
Since opening in 2021.
Years running
Programs completed
Max cohort size
Cohorts per year
DICT Thailand EdTech Recognition
Applied AI Education · 2023
Thailand Software Industry Association Member
Professional Education Division
Bangkok Startup Week Featured Partner
Technical Education Track · 2024
See which program fits your schedule
Send us a note with your background and what you want to build. We will tell you which program makes sense.
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