Three Programmes.
One Clear Direction.
Each programme is built for a specific starting point. Compare them here — scope, process, outputs, and pricing all listed plainly.
← HomeHow the Programmes Are Structured
Each programme at latentspacsdsd follows the same underlying logic: introduce a concept, apply it in a small guided exercise, then use it in a project that produces something you keep. The ratio of explanation to practice shifts as you move through material — by the end of any track, you're spending most of your time working, not reading.
The Starter programme is the most guided — exercises are tightly scoped and feedback is frequent. The ML Build Series gives more room for your own decisions at each module stage. The Capstone programme is the most open: you set the project direction with your mentor and make the key choices throughout.
Feedback is woven in at every stage. In the Starter and Build tracks this happens as written comments on submitted work. In the Capstone it happens in sessions where you and your mentor go through the code together.
Concept Introduction
Material is presented in plain language with code examples. Jargon is explained when introduced, not assumed.
Guided Practice
Structured exercises with clear scope. You apply the concept with guardrails before working more openly.
Project Work with Feedback
A project ties together the module's material. You submit it, receive specific feedback, and it becomes part of your portfolio.
Iteration and Review
Based on feedback, you revise or extend your work. Understanding comes from applying notes, not just reading them.
Process Steps
Python basics — variables, data types, loops, functions, file handling
Introduction to data with Pandas and NumPy — loading, cleaning, exploring
Core ML concepts — what a model is, how training works, basic evaluation
First simple classification project with guided scoping and written review
Coding & AI Starter Programme
A beginner-friendly programme building Python skills and a clear understanding of core machine-learning ideas through small, guided projects. Suited to people starting from little or no coding background. Includes structured exercises and reviewed work; results follow from steady practice.
- No prior coding background required to begin
- Python and ML fundamentals in a single connected track
- Written feedback on every exercise submission
- Portfolio project at the end of the track
Hands-On ML Build Series
A project-led series for learners with basic Python, covering data handling, model building, and evaluation. Each module ends with a portfolio project and written feedback. Designed for methodical, practical learning rather than shortcuts.
- Requires basic Python familiarity before starting
- Covers data pipelines, feature engineering, and model evaluation
- Portfolio project at every module — not just at the end
- Written feedback focused on decisions and reasoning
Process Steps
Data collection and cleaning with Pandas — real datasets, realistic problems
Feature engineering and exploratory analysis — what signals matter and why
Model selection and training with scikit-learn — classification and regression
Evaluation, iteration, and module portfolio project with written feedback
Process Steps
Project scoping session — defining the problem, data sources, and success criteria
Build cycles with regular mentoring sessions and code review at each stage
Mid-project review — addressing bottlenecks, refining approach based on early results
Portfolio write-up and final review session — project documentation guidance included
Mentored Capstone Programme
A longer track where learners build a complete AI project with regular one-to-one mentoring, code review, and portfolio guidance. For committed learners who want focused support over several weeks. Progress depends on each learner's time and effort.
- Regular one-to-one sessions with a named mentor
- You choose the project direction with your mentor's input
- Code review and architectural feedback throughout
- Portfolio documentation guidance at completion
Which Programme Fits?
Use this to quickly compare what each track includes and identify which suits your current starting point.
| Feature | Starter ฿4,400 |
ML Build ฿10,000 |
Capstone ฿30,500 |
|---|---|---|---|
| Best for | No coding background | Basic Python users | Committed learners with Python & ML basics |
| Python & ML fundamentals | |||
| Portfolio project included | |||
| Written feedback on submissions | |||
| Multiple portfolio projects | |||
| One-to-one mentoring sessions | |||
| Learner-directed project scope | Partly | ||
| Typical duration | 6–10 weeks | 8–14 weeks | 10–16 weeks |
Not sure which applies to you? Send us a message — we'll help you work it out.
Shared Across All Programmes
Learner Data Privacy
All submitted work and personal data handled under Thailand's PDPA. Submissions are not shared or used outside the programme relationship.
Regular Curriculum Review
Programme content reviewed every six months. Exercises and library versions updated to stay current with Python ecosystem changes.
Specific Feedback Standard
Feedback policy requires comments to address the specific submission, not apply a template. Feedback quality is checked across submissions each cycle.
Work Ownership
All code and project files produced during a programme are the learner's own. We don't claim any rights over submitted work.
Support Responsiveness
Questions about exercises or programme content receive a response within two working days. Mentoring sessions booked within one week of request.
Transparent Scope
Each programme page accurately describes what's covered, what isn't, and what a learner should realistically expect to produce by the end.
Straightforward Pricing
All fees listed here. No additional costs during the programme.
Coding & AI Starter
฿4,400
One-time programme fee
- Python fundamentals track
- Core ML concepts
- Guided exercises with feedback
- One portfolio project
- Completion record
Hands-On ML Build
฿10,000
One-time programme fee
- Data handling and pipelines
- Model building and evaluation
- Feedback on each module submission
- Multiple portfolio projects
- Completion record
Mentored Capstone
฿30,500
One-time programme fee
- One-to-one mentoring sessions
- Full AI project build
- Code review throughout
- Portfolio documentation guidance
- Completion record
Ready to Start a Conversation?
All programme enrolments begin with a brief message. Tell us which track interests you and where you're starting from.
Get in Touch