Course Tracks
Three tracks, one connected path through AI development
Each track is a complete course with its own scope and outcome. They're also designed to follow one from another — so completing Track 01 puts you in a strong position for Track 02, and Track 02 for the Capstone.
← Back to HomeOur Methodology
How the curriculum is structured
The three Codeloom tracks are designed around a node-and-layer principle: each topic prepares the ground for the next, and each track prepares the learner for the one that follows. The goal is that nothing appears without context, and no concept is introduced before the foundations that support it are in place.
Exercises within each track use real datasets and require open-ended decision-making rather than step-following. Project work is reviewed by practitioners — the feedback addresses the reasoning behind decisions, not just whether the output matches a key.
All tracks are delivered online with self-paced access within milestone windows. The milestone structure keeps progress on track without requiring learners to attend at fixed times.
Sequential design
Each track is built to follow the previous one. Topics connect across the full path, not just within a single course.
Real engineering practice
Exercises require decisions, not step-following. Code is reviewed by practitioners against professional standards.
Milestone pacing
Self-paced access within defined windows keeps learning on track without fixed attendance requirements.
Regular content review
Curriculum is reviewed against current tooling every six months. Topics that have become outdated are updated, not left in place.
Track 01
Foundations of AI Development
฿3,740
A structured starter course covering core programming for data work, the fundamentals of machine learning, and how modern models are built and evaluated. Paced for steady learning with practical, reviewed exercises. Includes a small project and community study group.
What's covered
How the track progresses
Programming foundations — working with data in Python, writing reusable code, understanding common data structures
ML concepts — supervised and unsupervised approaches, training loops, loss functions
Model evaluation — metrics, validation strategies, understanding what the numbers mean
Capstone project — a small, self-contained task reviewed by the instructional team
Best for
Learners who are new to machine learning and want a structured start. Previous programming experience is helpful but not required — the track introduces the relevant concepts from the beginning.
Enquire About Track 01Track 02
Applied Model Building
฿7,140
A project-based course where learners build, train, and assess working models on real datasets, with mentor feedback at each milestone. Focused on practical skills and good engineering habits. Includes code reviews and a portfolio-ready project.
What's covered
How the track progresses
Dataset selection and preparation — working with real data that hasn't been pre-cleaned for you
Model build and training — applying the right approach for the data and the problem framing
Milestone review — written feedback from a practitioner on your approach and code quality
Portfolio project completion — a substantive, documented piece of work reviewed by the team
Best for
Learners who have covered the fundamentals — either through Track 01 or equivalent prior study — and are ready to work on real problems with a practitioner in the feedback loop.
Enquire About Track 02Track 03
Capstone & Mentorship Track
฿11,560
An extended track combining advanced topics, a substantial capstone project, and one-to-one mentorship from working practitioners. Designed for learners ready to deepen their craft over several weeks. Includes structured feedback and a presentation of the finished work.
What's covered
How the track progresses
Advanced content — topics selected in part based on the learner's direction and capstone scope
Capstone scoping — working with the assigned mentor to define the project and its evaluation criteria
Build phase — regular one-to-one sessions and written feedback throughout the capstone arc
Final presentation — a structured presentation of the completed work to the mentorship team
Best for
Learners who have solid foundations and project experience and want to work through a substantial piece of AI development with direct guidance from a practitioner over several weeks.
Enquire About Track 03Track Comparison
What each track includes
| Feature | Track 01 ฿3,740 |
Track 02 ฿7,140 |
Track 03 ฿11,560 |
|---|---|---|---|
| Core curriculum access | |||
| Practitioner-reviewed project | |||
| Community study group | |||
| Milestone mentor feedback | |||
| Code review by practitioner | |||
| One-to-one mentorship sessions | |||
| Substantial capstone project | |||
| Final presentation |
Standards Across All Tracks
Shared principles that apply to every course
Privacy & data handling
Learner data is collected and stored in line with Thai personal data protection requirements. No data is sold or shared with third parties for marketing purposes.
Six-month curriculum review
All three tracks are reviewed against current AI tooling and practice at least every six months. Content that has become outdated is updated before the next cohort begins.
Feedback collection
Each track includes structured feedback points where learners can report what's unclear or where the pacing doesn't feel right. That feedback directly informs curriculum changes.
Responsive support
Enquiries to [email protected] are responded to on working days. Administrative questions about enrolment, pacing, or course scope are handled by the Bangkok office team.
Transparent course scope
What each track covers is published in full before enrolment. There are no hidden modules, no add-on requirements, and no ambiguity about what the price includes.
Online, worldwide access
All three tracks are delivered fully online. Learners access materials and submit work through a consistent platform without geographical restriction.
Pricing
Course fees in Thai Baht
All prices are one-time. No subscriptions, no hidden fees.
Track 01
Foundations
฿3,740
one-time fee
- Core curriculum
- Reviewed exercises
- Small final project
- Community study group
Track 02
Applied Building
฿7,140
one-time fee
- Full curriculum access
- Real dataset projects
- Milestone mentor feedback
- Practitioner code review
- Portfolio-ready project
Track 03
Capstone & Mentorship
฿11,560
one-time fee
- Advanced AI topics
- One-to-one mentorship
- Substantial capstone project
- Structured feedback arc
- Final presentation
Not sure where to start?
Tell us about your background and we'll help you choose
Send a message with where you are now — what you know, what you've tried, what you're hoping to build — and we'll suggest which track makes sense as a starting point.
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