Three Tracks.
One Clear Progression.
Each track is built for a specific experience level and learning goal. Choose based on where you are right now — not where you'd like to be. We can help you work out which fits if you're not sure.
← Back to HomeHow Every Track Works
The structure is consistent across all three tracks — what changes is the depth, the assumed background, and the focus of the project work.
Structured Modules
Clear module sequence — you know what each session builds on and what it leads to.
Weekly Check-ins
One dedicated mentor, same person throughout. Weekly sessions, plus async messaging between.
Code Reviews
Mentors review your actual work, not just completion status. Specific feedback on what you wrote.
Portfolio Output
Projects built at every stage. You finish with real work to show, not a completion screen.
AI Foundations Track
An entry-level programme covering core programming, data handling, and the building blocks of machine learning, with weekly mentor check-ins. This track is designed for motivated beginners — people who are committed to steady, hands-on effort rather than looking for a shortcut. Expect to spend 8–12 hours per week. Includes practice projects and access to a supportive learner community throughout.
What This Track Covers
- Core programming fundamentals — variables, control flow, functions, data structures
- Working with data — reading, cleaning, and exploring datasets
- Introduction to machine learning concepts and common algorithms
- Practice projects applied to real datasets with mentor review
- Weekly mentor check-ins throughout the full programme
Track Process
Pre-track conversation
Brief discussion to confirm this track fits your background and pace expectations.
Module delivery + practice
Work through structured modules with exercises and small projects at each stage.
Weekly mentor sessions
Review progress, get code feedback, ask questions, and agree on the next focus area.
Track completion
Finish with a portfolio of practice projects and a completion record from Neuronest.
Best For
- People with basic computer literacy but no programming background
- Learners who want structured guidance rather than figuring it out alone
- Those who want to understand ML before deciding whether to go deeper
Applied Machine Learning Studio
A project-based course where learners build and evaluate real models — from data preparation through to deployment basics — guided by mentors. This track suits people with foundational programming who want practical depth. Includes code reviews on your submissions and a portfolio of completed projects that reflects real applied work.
What This Track Covers
- Data preparation pipelines — handling messy real-world data
- Model selection, training, and rigorous evaluation methods
- Introduction to deployment — moving a model from notebook to something usable
- Code reviews from working practitioners on every major project
- Portfolio of completed applied projects with documented approaches
Track Process
Background assessment
We check that your current programming foundation is strong enough for this track's starting point.
Applied project sequence
Build through a series of real ML projects, each increasing in complexity and scope.
Weekly code review sessions
Your mentor reviews your project code each week with specific written and verbal feedback.
Portfolio documentation
Each completed project is documented in your portfolio with approach notes and results.
Best For
- Developers or analysts who can already code but haven't done applied ML work
- Learners who want a genuine portfolio, not just course completion
- Those considering the Career-Readiness track who want to build a foundation first
AI Engineering Career-Readiness Track
An advanced, mentor-supported programme focused on production-minded AI development, system design, and a strong project portfolio. Includes interview practice and peer collaboration. This is a significant commitment of time and money — we're direct about that. We support your preparation thoroughly; career outcomes depend on your own effort, the work you produce, and conditions in the market.
What This Track Covers
- Production AI system design — scalability, maintainability, monitoring
- Advanced model development with deployment and evaluation pipelines
- Interview preparation — technical questions, system design discussions, coding sessions
- Peer collaboration and code review across the cohort
- Strong project portfolio with documented engineering decisions
Track Process
Prerequisite review
This track assumes solid applied ML experience — we verify this before enrolment to protect your time and money.
Production systems modules
Work through system design, deployment architecture, and production monitoring topics.
Peer review + interview prep
Peer code reviews within the cohort, plus dedicated interview preparation sessions with your mentor.
Portfolio completion
Finalise and document your project portfolio — the primary output of the track.
Best For
- Engineers with applied ML experience who want to work on production AI systems
- Those preparing for AI engineering roles who want structured preparation
- Learners who have completed the Applied ML Studio and want to go further
Track Comparison
Use this to identify which track fits your current level — not where you want to be.
| Feature | Foundations ฿3,600 |
ML Studio ฿18,000 |
Career-Readiness ฿35,500 |
|---|---|---|---|
| Prior coding needed | Not required | Yes | Yes (strong) |
| Weekly mentor sessions | |||
| Code reviews | Project-based | Per submission | Per submission + peer |
| Portfolio projects | Practice projects | Applied projects | Production-focused |
| Deployment topics | Intro to deployment | Advanced deployment | |
| Interview preparation | |||
| System design modules | |||
| Peer cohort review |
Shared Across All Tracks
Learner Data Privacy
Project work, progress records, and contact information are kept confidential. No sharing with third parties beyond what's stated in our privacy policy.
Curriculum Updated Twice Yearly
Content is reviewed and updated at least every six months. Mentors flag outdated material in real time during sessions.
Controlled Cohort Sizes
We limit intake when mentor capacity is reached. Quality of attention matters more than volume of enrolments.
Honest Pre-Enrolment Conversations
Before you pay for anything, we encourage a conversation to confirm the track is appropriate for your background and pace.
Thailand Timezone Delivery
Mentor sessions scheduled in ICT. No off-hour commitments. Designed for learners in Bangkok and across Thailand.
English Language Delivery
All track content, mentor sessions, and code reviews are conducted in English — consistent across every level.
Transparent Track Pricing
All prices in Thai Baht. Everything included — no platform fees or add-on tiers.
AI Foundations Track
- Full curriculum access
- Weekly mentor sessions
- Practice projects
- Community access
- Completion record
Applied ML Studio
- Full curriculum access
- Weekly mentor sessions
- Code reviews per project
- Project portfolio
- Community access
Career-Readiness Track
- Full curriculum access
- Weekly mentor sessions
- Code reviews + peer review
- Interview preparation
- System design modules
Not Sure Which Track Fits?
Send us a message describing your current background and what you're hoping to learn. We'll give you a straight answer about which track makes sense — or whether to wait and build more foundation first.
Send an Enquiry