Course Tracks

Three Tracks, Each One Purposefully Designed

From a first structured look at machine learning through to a guided capstone with one-to-one mentorship — each track has a clear scope, a real project, and reviewed exercises throughout.

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Our Approach

How Each Track Is Structured

Synaptiq courses are built around a simple idea: you should be doing the work, not just watching it. Every module leads to an exercise. Every exercise gets reviewed. The next module doesn't open until the review is complete.

This means feedback is tight and the path stays honest. If something in an earlier module hasn't settled, the review process usually surfaces it before it creates trouble later. That's the main practical advantage of keeping cohorts small.

Each track ends with a project — something real, with documented decisions and reviewed code. The standards for completion are defined upfront so there's no ambiguity about what "done" means.

Module-Based Learning

Content structured in discrete, reviewable units

Written Feedback

Every submission gets a human response, not automation

Sequential Tracks

Each track builds directly on the previous one

Real Project Output

Completion means producing something concrete

Track 01

Foundations of AI Development

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.

Core programming concepts for data manipulation and analysis
Introduction to machine learning and model types
Evaluation methods and reading model performance
Reviewed exercises after each module
Small group study community throughout

~5–6 weeks

฿4,420

Enquire About Track 01

Process steps

Environment setup and data handling basics

ML concepts — supervised and unsupervised approaches

Building and evaluating a first model

Final project with mentor review

Process steps

Dataset selection and exploratory analysis

Feature engineering and model training

Evaluation, iteration, and code review

Portfolio project documentation and submission

Track 02

Applied Model Building

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.

Working with real datasets from selection through cleaning
Mentor feedback at each project milestone
Structured code review covering quality and engineering habits
Portfolio-ready output with documented decisions
Assumes Track 01 background or equivalent

~7–8 weeks

฿7,480

Enquire About Track 02

Track 03

Capstone & Mentorship Track

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.

Advanced topics — model deployment, pipeline design, evaluation at scale
One-to-one sessions with an active practitioner mentor
Substantial capstone project with defined scope and criteria
Structured feedback at each project phase
Final presentation reviewed by mentor

~10–12 weeks

฿10,880

Enquire About Track 03

Process steps

Advanced module work and 1-to-1 scoping session

Capstone design, planning, and mentor check-in

Build phase with structured milestone feedback

Final presentation and mentor review session

Compare Tracks

Which Track Is Right for You?

Feature	Track 01 ฿4,420	Track 02 ฿7,480	Track 03 ฿10,880
Module-based curriculum
Reviewed exercises
Study group community		—	—
Real dataset project	Starter
Code review	—
1-to-1 mentor sessions	—	—
Capstone project + presentation	—	—

Best for

Track 01

Someone new to ML who wants a structured, paced introduction with support from a study group.

Best for

Track 02

Someone with foundational knowledge who wants to produce a real, reviewed project with mentor feedback.

Best for

Track 03

Someone ready to take on a substantial challenge with direct guidance from a practitioner over 10–12 weeks.

Across All Tracks

Standards Applied to Every Course

Data Privacy

Learner information is handled with care and not shared with third parties. See our privacy policy for details.

Curriculum Maintenance

Materials are reviewed and updated between cohorts to reflect current tools, library versions, and field practice.

Responsive Support

Questions sent during office hours are responded to within one business day. We aim for shorter on busier days.

Practical Over Theoretical

Every concept is introduced alongside a task. Theory without practice doesn't produce competence — we keep the two together.

Completion Criteria

What "done" means for each project is defined at the start. No ambiguity about whether the work meets the bar.

Cohort Size Control

Groups stay small so feedback is personal and mentors can track each learner individually. We cap enrolment per cohort.

Pricing

One Payment Per Track

All prices are in Thai Baht (฿). No subscriptions, no hidden additions. Pay once and access everything included in that track.

Track 01

Foundations

฿4,420

All course modules
Reviewed exercises
Starter project
Study group access

Enquire

Track 02 Popular

Applied Building

฿7,480

All course modules
Reviewed exercises
Mentor milestone reviews
Code review session
Portfolio project output

Enquire

Track 03

Capstone Track

฿10,880

All course modules
Reviewed exercises
1-to-1 mentor sessions
Capstone project
Final presentation review

Enquire

Ready to Start

Not Sure Where to Begin? Ask Us.

Tell us about your background and what you're hoping to build — we'll point you toward the right starting track.

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